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Master’s Thesis

Energy Engineering

Supplying the energetic needs of the farm Can Barrina (Osona) by transforming cattle raising and agricultural

wastes into biogas: Technical study of applicable technologies

REPORT

Author: Vittorio Sbarbaro Sola Director: Jordi Llorca Piqué Speaker: - Announcement: June 2020

Escola Tècnica Superior d’Enginyeria Industrial de Barcelona

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Supplying the energetic needs of Can Barrina Pàg. iii

Abstract

On farms around the world, millions of tons of livestock and agricultural waste are constantly

generated of which, although a significant part of them can be reused as fertilizers and

fertilizers, there is a considerable amount that does not have a clear or defined usage/purpose.

Indeed, there is a huge energy potential – unexplored if compared to what it could suppose in

quantitative absolute terms – in the reuse of this wastes for biogas generation.

This Master's Thesis aims to study and size an Energy Generation System – electrical and

thermal – based on the production of biogas using an anaerobic digester: Taking advantage

of the wastes and resources associated to the nrmal operation of the farm Can Barrina, located

in Santa Cecília de Voltregà (near Vic). This project models the real thermal and electrical

demand of this farm houly, by using Excel and MATLAB computer tools; in order to know what

would be the optimal system to transform this wastes/resources into energy available for self-

consumption.

Once the hourly demand is known, the available resources and waste are studied in detail to

select those that boost biogas production yield, optimizing it. Finally, three different types of

conversion technologies (to transform biogas into final energy) are compared: A Solid Oxide

Fuel Cell, a conventional gas cycle with gas micro-turbine that burns the biomethane resulting

from refining the biogas, and finally the same fuel cell with a gas micro-turbine that uses the

exhaust gases from the cell to increase the electrical performance of the system.

Consequently, a technical, economic and environmental study is carried out to analyse the

viability of the installation for the most suitable system considering Can Barrina’s needs: Being

clearly the last conversion technology presented the best option following the technic and

economic criteria.

Once the necessary calculations have been performed, from a technical and environmental

point of view the percentage of self-consumption covered by the system would generate

significant energy savings and mitigation of polluting gases. Economically, the results obtained

show a strong dependence on the variability of the harvesting periods of maize to amortize the

initial investment, since maize production cannot be predicted at all and a series of bad

harvests could jeopardize the economic viability of the project (even if positive results are more

likely, risk must be contemplated).

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Resum

A les granges d’arreu del món es generen constantment milions de tones de residus ramaders

i agrícoles del quals, si bé una part important d’ells es poden reutilitzar com a adobs i

fertilitzants, hi ha una quantitat considerable que no té un ús totalment definit o clar. De fet, hi

ha un grandíssim potencial energètic – inexplorat en comparació a lo que podria aportar en

termes absoluts – en la reutilització d’aquests residus per a la generació de biogàs.

Aquest Treball de Final de Màster té com a objectiu l’estudi i dimensionament d’un Sistema

de Generació d’Energia – elèctrica i tèrmica – basat en la producció de biogàs mitjançant un

digestor anaeròbic: Aprofitant els residus i recursos de la granja Can Barrina, situada a Santa

Cecília de Voltregà (vora Vic). En aquest projecte es modelitza la demanda tèrmica i elèctrica

real d’aquesta granja hora a hora mitjançant les eines informàtiques Excel i MATLAB, per així

saber quin seria el sistema òptim per transformar aquests residus/recursos en energia

disponible per l’autoconsum.

Un cop coneguda la demanda, s’estudien detalladament els recursos i residus disponibles per

seleccionar aquells que potencien la producció de biogàs, optimitzant-la. Finalment, es

comparen tres tipus diferents de sistemes per convertir aquest biogàs en l’energia final

desitjada, que són: Una pila de combustible del tipus “Solid Oxide Fuel Cell”, un cicle de gas

convencional amb micro-turbina de gas que crema el biometà resultant de refinar el biogàs i

finalment la mateixa pila de combustible amb una micro-turbina de gas que empra els gasos

d’exhaustió de la pila per augmentar el rendiment elèctric del sistema.

Conseqüentment, es realitza un estudi tècnic, econòmic i ambiental per analitzar la viabilitat

de la instal·lació pel sistema que utilitza la tecnologia de conversió més adequada a les

necessitats de Can Barrina: Sent clarament l’últim sistema de conversió presentat el que millor

s’adapta a les necessitats de la granja.

Un cop realitzat els càlculs necessaris, des del punt de vista tècnic i ambiental el percentatge

d’autoconsum cobert pel sistema generaria importants estalvis energètics i d’emissions de

gasos contaminants. Econòmicament, els resultats obtinguts mostren una forta dependència

en el compliment de varis anys amb bones collites per assegurar la viabilitat econòmica de la

instal·lació, vist que la producció de blat de moro a Can Barrina és limitada i depèn dels

excedents dels anys amb sobreproducció.

Supplying the energetic needs of Can Barrina Pàg. v

Resumen

En las granjas de todo el mundo se generan constantemente millones de toneladas de

residuos ganaderos y agrícolas de los cuales, si bien una parte importante de ellos se pueden

reutilizar como abonos y fertilizantes, hay una cantidad considerable que no tiene un uso

totalmente definido o claro. De hecho, hay un grandísimo potencial energético - inexplorado

en comparación a lo que podría aportar en términos absolutos - en la reutilización de estos

residuos para la generación de biogás.

Este Trabajo de Final de Máster tiene como objetivo el estudio y dimensionamiento de un

Sistema de Generación de Energía - eléctrica y térmica - basado en la producción de biogás

mediante un digestor anaeróbico: Aprovechando los residuos y recursos de la granja Can

Barrina, situada en Santa Cecília de Voltregà (al lado de Vic). En este proyecto se modeliza

la demanda térmica y eléctrica real de esta granja hora a hora mediante las herramientas

informáticas Excel y MATLAB, para así saber cuál sería el sistema óptimo para transformar

estos residuos/recursos en energía disponible para el autoconsumo.

Una vez conocida la demanda, se estudian detalladamente los recursos y residuos

disponibles para seleccionar aquellos que potencian la producción de biogás, optimizándola.

Finalmente, se comparan tres tipos diferentes de sistemas para convertir este biogás en la

energía final deseada, que son: Una pila de combustible del tipo "Solid Oxide Fuel Cell", un

ciclo de gas convencional con microturbina de gas que quema el biometano resultante de

refinar el biogás y finalmente la misma pila de combustible con una microturbina que emplea

los gases calientes resultantes del funcionamiento normal de la pila de combustible para

aumentar el rendimiento eléctrico del sistema.

Consecuentemente, se realiza un estudio técnico, económico y ambiental para analizar la

viabilidad de la instalación por el sistema que utiliza la tecnología de conversión más

adecuada a las necesidades de Can Barrina: Siendo claramente el último sistema de

conversión presentado el que mejor se adapta a las necesidades de la granja.

Una vez realizado los cálculos necesarios, desde el punto de vista técnico y ambiental el

porcentaje de autoconsumo cubierto por el sistema generaría importantes ahorros

energéticos y de emisiones de gases contaminantes. Económicamente, los resultados

obtenidos muestran una fuerte dependencia en el cumplimiento de varios años con buenas

cosechas para asegurar la viabilidad económica de la instalación, visto que la producción de

maíz en Can Barrina es limitada y depende de los excedentes de los años con

sobreproducción.

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Supplying the energetic needs of Can Barrina Pàg. vii

Summary

ABSTRACT __________________________________________________ III

RESUM _____________________________________________________ IV

RESUMEN __________________________________________________ V

SUMMARY _________________________________________________ VII

1. GLOSSARY ______________________________________________ 1

2. PREFACE ________________________________________________ 6

2.1. Project Origin .................................................................................................. 6

2.2. Motivation ....................................................................................................... 7

2.3. Prerequisites ................................................................................................... 8

3. INTRODUCTION ___________________________________________ 9

3.1. Objectives of the project ............................................................................... 13

3.2. Area of application ........................................................................................ 14

4. ENERGY SUPPLY ________________________________________ 15

4.1. Description of Can Barrina ........................................................................... 15

4.1.1. Description of the activities developed ............................................................ 17

4.1.2. Description of the existing facilities .................................................................. 22

4.2. Energetic loads associated to this activity .................................................... 27

4.2.1. Cows’ associated loads ................................................................................... 27

4.2.2. Pigs’ associated loads ..................................................................................... 31

4.2.3. Agricultural and other loads ............................................................................. 31

4.3. Load flow study............................................................................................. 32

4.3.1. Dependence on meteorological conditions ..................................................... 34

4.3.2. Electrical demand............................................................................................ 38

4.3.3. Thermal demand ............................................................................................. 55

5. BIOGAS PRODUCTION ____________________________________ 63

5.1. Transformation of residues into biogas ........................................................ 63

5.1.1. Usable wastes and resources produced in the farm’s normal activity ............. 63

5.1.2. Influence of ripening, silage and composition of the crops .............................. 64

5.1.3. Influence of the characteristics of manure ....................................................... 70

5.1.4. Anaerobic digestion and biogas production ..................................................... 72

5.1.5. Production of coproducts ................................................................................ 79

5.1.6. Sizing and operation of the biodigester ........................................................... 81

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5.2. Energetic needs of the biodigester .............................................................. 88

5.2.1. Electrical demand ............................................................................................ 89

5.2.2. Thermal demand .............................................................................................. 92

6. BIOGAS UPGRADING ____________________________________ 101

6.1. Biogas quality requirements ....................................................................... 101

6.1.1. SOFC biogas quality requirements ................................................................ 101

6.1.2. Gas cycle biogas quality requirements ........................................................... 103

6.2. Upgrading technology ................................................................................ 104

6.2.1. GCU selected for the SOFC alternative ......................................................... 104

6.2.2. GCU selected for the gas cycle alternative .................................................... 106

7. APPLICABLE CONVERSION TECHNOLOGIES _______________ 110

7.1. Introduction to the alternatives assessed ................................................... 110

7.1.1. Conversion using a fuel cell ........................................................................... 110

7.1.2. Conversion using a gas cycle ........................................................................ 113

7.2. Alternative 1: SOFC ................................................................................... 115

7.2.1. Description of SOFC ...................................................................................... 115

7.2.2. Sizing and results of alternative 1 .................................................................. 119

7.2.3. CO2 sequestration .......................................................................................... 124

7.3. Alternative 2: Gas cycle ............................................................................. 126

7.3.1. Description of gas cycle ................................................................................. 126


7.4. Alternative 3: SOFC combined with a gas turbine ..................................... 135

7.4.1. Description of SOFC with Micro-GT ............................................................... 135


7.5. Technical comparison between the alternatives ........................................ 143

8. ECONOMIC ANALYSIS ___________________________________ 146

8.1. Economic comparison between technologies ............................................ 146

8.1.1. Economic study EGS 1 .................................................................................. 150



8.2. Detailed economic analysis for the EGS 3 ................................................. 157

9. ENVIRONMENTAL ANALYSIS _____________________________ 163

CONCLUSIONS _____________________________________________ 167

ACKNOWLEDGEMENTS ______________________________________ 170

BIBLIOGRAPHY _____________________________________________ 171

Supplying the energetic needs of Can Barrina Pàg. 9

Bibliographic references ...................................................................................... 171


1. Glossary

The basic acronyms, mathematical symbols and Greek letters (respectively) used along this

project are listed below in order of appearance in this report. The units expressed in this

glossary are in all case in the International System (S.I.), but in the calculations carried out in

this project other units may have been used.

Acronyms:

EGS Energy Generation System

RES Renewable Energy Sources

GHGs Greenhouse Gases

VRE Variable Renewable Energies

NG Natural Gas

HP Horsepower

SOFC Solid Oxide Fuel Cell

MCFC Molten Carbonate Fuel Cell

VS Volatile Solid

DM Dry Matter

BMP Biochemical Methane Potential

TS Total Solid

C/N Carbon/Nitrogen relation

SBP Biogas Production Rate

GCU Gas Cleaning Units

HTF Heat Transport Fluid

GT Gas Turbine

CHP Combined Heat and Power

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CCPP Combined Cycle Power Plant

SOFC-MGT Solid Oxide Fuel Cell with Micro-Gas Turbine

PR Pressure Ratio

FC Fixed Costs

VC Variable Costs

NPV Net Present Value

LCA Life Cycle Assessment

GWP Global Warming Potential

Symbols:

T Time [s]

𝑡̅ Mean time of one action [s]

𝑁𝑐𝑜𝑤𝑠′ Number of cows used for milking porpuses

𝑁𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑚𝑎𝑐ℎ Number of milk extraction machines

𝑡𝑡𝑜𝑡𝑎𝑙 Total time of an action [s]

Tamb Ambient temperature [K]

m’ Slope of the energy consumption line’s equation

Ei Total electricity consumption of a month “i"

Mi Total electricity consumption of the main devices in a month “i"

Oi Total electricity consumption of the other devices in a month “i"

𝑇ℎ,𝑖̅̅ ̅̅ Hourly mean temperature for the hour “h” of the month “i”

Pfanm,h,d Power delivered by the fans at a specific hour “h” of day “d” and month “i”

Bm,h,d Boolean value equal to 1 if fans are working at a specific hour “h” of day “d”


and month “i”

Nfans Number or unities of fans for cows

Pnom Nominal power of any device (is used for multiple devices/motors) [W]

Econs Energy consumption (total or for a specific load), can be electric or thermal [J]

r Radius of a circumference (of a cylinder, sphere…) [m]

L Altitude of a geometric form or width of a specific layer [m]

V Volume of a specific form [m3]

Ti Internal temerature temperature of a control volume [K]

vwind Wind speed [m/s]

h Convection heat transfer coefficient [W/(m2·K)] or altitude of a spherical cap [m]

Rtot Total thermal resistance [K/W]

U Overall heat transfer coefficient [W/(m2·K)]

Re Reynolds number

Nu Nusselt number

Pr Prandlt number

k Thermal conductivity [W/(m·K)]

qr Heat transfer rate [W]

Tf Final temperature [K]

Tgrid Temperature of the water from the grid [K]

Eth Thermal energy or thermal demand [J]

m Mass [kg]

Cp Specific heat [J/(kg·K)]

A Area [m2]

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hi Inner convection heat transfer coefficient [W/(m2·K)]

ho Outer convection heat transfer coefficient [W/(m2·K)]

Tsol-air Temperature on the boundary layer between a wall and the air in contact with

it [K]

It Solar irradiance [W/m2]

a Mean radius of a spherical cap with rectangular base [m]

P Pressure [Pa]

Q Thermal energy or heat [J]

z Specific depth in the soil [m]

Tm Mean temperature of the soil [K]

As Oscillation of superficial temperature [K]

t0 Gap of time between initial and calculated value [s]

α Thermal diffusivity of the soil [m2/s]

tpayback Payback time for an investment [s]

i Interest or inflation rate

Greek letters:

μ Viscosity [kg/ (m·s)]

ρ Density [kg/m3]

𝜂 Efficiency in p.u or %

ε Reflectivity p.u. or %

σ Boltzmann constant [W/(m2·K4)]

αs Absortivity in p.u. or %

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2. Preface

2.1. Project Origin

The origin of this project comes from an idea that some classmates and me started to develop

for carrying out the main project of the subject “Hydrogen and Fuel Cells”. Among many other

options, we chose to go for a project named “Countryside house or farm operated with H2”,

which would be focused on implementing a Fuel Cell system of our choice with the idea of

operating it with hydrogen.

One of the things that made that project different from many of those done throughout the

master’s degree was that the data must be obtained from a real installation, organisation or

manufacturer; making all the projects executed by the different teams more realistic. Therefore,

we searched for a real countryside house or farm. At this point, I personally proposed to contact

one acquaintance of mine who owns a large farm located in Santa Cecilia de Voltregà, near

Vic. The result was really satisfactory since he acceded to share all the information we were

looking for regarding his business (electric bills, thermal loads, existing facilities and

dimensions, wastes of the farm…).

At the very beginning, we just thought about finding some hydrogen suppliers and the Fuel

Cell that would fit better with the existing facilities in this farm (Can Barrina), but rapidly we

noticed that that project could go far beyond this simple scope. Why?

Because farms with agricultural and livestock activities usually have many residues such as

unused crops (or parts of the different cereals or plants), animal slurry (liquid and solid) and

other kind of organic debris; wastes that can be perfectly used to be transformed into raw

biogas by performing an anaerobic digestion. Consequently, we push ahead our interest for

fuel cells that can work with methane (CH4) – not pure preferably for the reasons explained

later on – instead of those which works just with pure H2; considering that doing a grey

reforming from the CH4 molecule needs many expensive steps before using it in a conventional

technology such as the Proton Exchange Membrane Fuel Cell (PEMFC).

Molten Carbonate and Solid Oxide Fuel Cells (MCFC & SOFC, respectively), supposed

undoubtedly an appealing technology for generating electricity and heat for feeding the

energetic consumption of the farm from raw biogas, and at this point the project took shape.

All the subsequent work was to calculate the new energetic needs that the farm would have

with the biodigester in charge of generating the biogas as well as the mix of substances that


are more suitable for producing it, the size of this digester, the amount of energy that it can

produced and how can be adjusted with the real consumption of Can Barrina. All of this led to

a technical analysis, and then also an economical one was executed.

In summary, Eduard Vila (farm’s owner) helped us to perform what has become our first task

realized in this university with a real client. He was interested in the results and now he knows

approximately how a system which transforms the farm’s wastes into energy by producing

biogas and transforming it into electricity and heat could fit with his existing facilities, as well as

an approximate prize for installing the fuel cell and the biodigester.

Obviously, the work we did is just a small fraction of all the work that it must be done to install

in reality a system as the one proposed. That’s why I considered to do this fascinating project

as my Master’s Thesis among many other ideas that I had in mind. In the next point it is

explained what motivated most for taking this choice.

2.2. Motivation

After delivering the final report of the project commented on the previous point, we all agreed

that the project was uncompleted: All the possible technical solutions to use the biogas were

not considered as this analysis was outside of the scope of the subject. In this Master’s Thesis

I can study with detail all the alternatives and which fits better to the studied case (technically

and economically), not just limiting the options to those which involve a Fuel Cell system. For

example, the raw biogas can be upgraded using a refining system which increase its purity,

and then it can be used in a gas turbine to produce electricity and heat. Besides, the

dimensioning of the infrastructure needed for the most suitable option as well as the energy

conversion steps would be known and deeply studied - not just approximated as we did in the

previous project (again, it was clearly out of the scope of that undertaking).

This is the reason why I selected this challenging Master’s Thesis with the hope that the results

could be useful for the farm’s owner which is now my client, and who knows, if they might even

become the base for a real project developed by a professional company. I reckon that the

part that I most like of this project is that all the data and calculations are done taking real

parameters from an existing business, which could lead to monetary savings and mitigation of

pollutant emissions associated to the activity of the farm.

Since I started to study engineering, I always have desired to drive my professional live to a

direction were my job could help to improve in some way the world where we live. It may seem

idyllic, but I believe that participating in any way on renewable-based projects is having a

positive impact to the world: Every step counts.

Personally, I have really high expectations on this project and I want it to be a benchmark of

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exigency for my future projects that would be developed in the professional world. This

motivates me a lot to try my best and strive.

2.3. Prerequisites

A comparison of different technologies to select which one of them fits better with the

requirements of the studied farm (taking into account the energetic loads, existing facilities,

meteorological conditions in the location of the farm, costs provided by the manufacturers…)

would require a single technical analysis of each of the technologies taken into account. Each

and every one of them with not exception, otherwise the results could not be the optimal ones.

Then, considering the technologies studied in this project, the most important knowledge -

acquired in the bachelor’s and master’s degree - was:

• Advance knowledge of energy balances and physics applied to engineering. This

becomes essential to calculate the different transformations of the energy from the

initial crops and slurries residues into electricity, considering the different conversions

of energy taking into account efficiencies and losses.

• Advance knowledge of load flow study, in order to assess the consumption in different

periods for the different components that make up the whole farm. Without analysing

the consumption thoroughly, it is impossible to calculate the optimal sizing of the

energy generation systems.

• Have some chemistry basics to perform the mass balances of the organic compounds

that would become raw biogas in an anaerobic digestion.

• Advance knowledge of thermodynamics laws and heat transfer; there are necessary

in different steps of the process such as the supply of heat to the biodigester, the

transfer of the excess energy from Fuel Cells systems or to transform the methane into

electricity by burning it in a gas cycle.

• Basic electrical knowledge. Despite not going into a comprehensive analysis of the

different electrical components of the farm, it is important to understand the electrical

fluxes and the generation of electricity in order to meet with the demand.

• Basic economical knowledge. An economic analysis is carried out, and to study the

feasibility of the project it is essential to be able to make some economical calculations.

• Informatic knowledge and programming skills. These arise as essential musts in order

to perform the different calculations in a software of data processing (Excel) and in a

mathematical multi-paradigm numerical computing programming language (MATLAB)

used to plot charts and implement algorithms to obtain the base and final results.


3. Introduction

Humankind has advanced tremendously as a specie in a really short time (compared to

chronological scale of the Earth): The discovering of its motor functions, the use of the practical

advantages of the fire, the setup of organized societies, the deep study of physical and

biological laws that govern the planet, the creation of trades, money, large cities, industry,

electricity, internet and who knows what’s coming next. In all of this process, there was a vital

step which occurred long time ago but without it all the posterior progress could not have been

possible: And this is the sedentarism stablished thanks to the agriculture and livestock

activities.

At the very beginning humans survived by recollecting fruits and other edible nutriments found

in forests, as well as from the meat obtained by hunting other animals. In that period survival

was our only purpose and when there was not more food in one area people just moved to

another one. Nonetheless, this era came to an end when the vast majority of humans started

to live in a specific place taking advantage of the fertile lands which could give large enough

crops to feed a large group of people. Besides, at some point these groups also started to

control the reproduction of some animal species making the hunting activities obsolete.

At this point, surviving by searching food was no longer a necessity and humankind could start

to specialize in other things since survival was taken for granted (excepting wars, natural

disasters, illnesses…). This led to progress until the point at which we are today. However, the

harvesting of the land and the obtaining of food are still the base of the human society, despite

all the technological advanced that have been possible thanks to the increased consumption

of the energetic resources exiting in the Earth. It does not seem drastic to say that if the global

food’s system collapses there can no longer be any future for humanity.

Nowadays, in the existing organization where all the services, jobs, activities and the major

part of industrial areas are located around super-large urban zones the agricultural sector

seems to have been displaced into rural areas far from the largest cities. According to Our

World in Data “more than the half of the world (55%) live in urban settings” [1]. In 2017 more

than 4,1 billion people were living in large cities. The tendency to increase the number of

people living in urban areas can be clearly appreciated in Fig. 3.1.

Following this explanation, it’s even more critical the fact that the World’s population – which

is 7,7 billion people right now - is expected to increase up to 9,7 billion people in 2050 and

could peak at nearly 11 billion in 2100 (according to the United Nations, [2]). The main

increased would happen in the largest cities, accentuating the tendency centralizing the society

in the areas with the smallest potential for producing basic needs such as food and drinkable

water.

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Fig. 3.1. Number of people living in urban-rural areas from 1960 to 2017 in the World. (Source: [1])

Consequently, if this tremendous increase of population’s takes place by the end of this century

the global demand of food and other basic needs in today’s standards of life (electricity, heat

power…) must increase in the same measure. Just focusing on the food’s part, it seems

obvious that the first measure to be done to face the increasing demand of different products

is to preserve the existing cropland, industries and the other related facilities. Then, once this

preservation is guaranteed, it would be essential to find new production centres (traditional

ones such as harvesting the land or reproducing animals or alternative ones not yet

discovered).

The target of this project is one of the many existing farms all over the world, which together

are in charge of supplying the greatest part of the food consumed by humans and many other

species that are also fed by humans (domestic animals, cattle, endangered animals…). For

this reason, ensuring the correct functioning of the farm would be all along this project a main

priority; Not only because our client would only pay for an Energy Generation System (EGS)

that would never interrupt his business, but also because the activity carried out in there is vital

for human development and survivance - as it has been explained along this section.

In this Master’s Thesis, an EGS for a farm - Can Barrina, in Santa Cecília de Voltregà, Osana

- is proposed. One of the main requirements of this system is that the energy generated by the

system comes from a green source that does not enhance the emission of dangerous

substances to the atmosphere, and then the question is: Why is this important?


The era of producing heat and electricity from fossil fuel-based resources will come to an end

soon or later; since coal, petroleum and natural gas (the most used fuels) are limited.

Nevertheless, burning all the reserves of the already available fossil fuels – intended as those

that can be extracted from Earth – would imply increasing the global temperature about 9,5 ºC

according to [3] (article published in Nature Climate Change) or about 10 ºC according to [4]

(article published in The Guardian journal). Both articles - and the common sense - lead us to

oversee the catastrophic consequences that this would generate to our planet: starting by the

loss of biodiversity, a tremendous increase of the sea level (with the consequent eviction of

billions of people), increment of droughts and desertification of many areas leaving them

uninhabitable and so on. The damages would then be disastrous for “human health, food

supply and global economy” according to The Guardian’s article.

Looking now for the information shared by Shell - one of the most important petrol and gas

companies in the world – in Shell Energy Scenarios to 2050 in the booklet Signals & Signposts

published in 2011 it can be appreciated which are the current scenarios in the emissions of

CO2 from now to 2050 (see Fig. 3.2). They argue that by 2050 the most possible scenarios

would be the Scramble scenario (where the most powerful energy companies keep on selling

fossil fuels and the vast majority of countries maintain or even increase their consumption

ratios of oil and coal) and the Blueprints scenario (where gas substitute a great part of coal

and oil – both more pollutant - and renewable energies start progressively to be installed in

different countries). [5]

Fig. 3.2. Estimated CO2 emissions from 2000 to 2100 in Scramble, Blueprints and IEA 450 scenarios.

(Source: [5]).

In any case, any of both scenarios proposed by Shell consider that the proposal signed in the

Paris Agreement of 2015 could be ever achieved (maintaining the total emissions of CO2 under

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450 ppm – parts per million). That scenario corresponds to the IEA 450 scenario and is

considered as unrealistic taking into account the current emissions and tendencies in the

world. [5]

Obviously, humankind is facing a tremendous danger that could jeopardize its survivance on

Earth in long term. For this reason, the only EGSs considered in this project were based on

Renewable Energy Sources (RES) that can help (on a small measure as long as it is only

implemented on a single farm) to mitigate the Greenhouse Gases (GHGs) emissions. Among

all the alternatives that could be used for generating electricity and heat in this farm, which has

enough available space and resources for making up a large range of possibilities, this project

is focused on transforming the cattle raising and the agricultural wastes into energy.

Instead of generating the electricity that the farm needs with photovoltaic (PV) solar panels

and the heat with a thermal solar collector (p.e. with some Flat Plates Collectors) or with regular

fossil fuel-based boilers, this Thesis Aims to study how the wastes generated on this activity

could be transformed into energy. This does not mean that exploiting other RES like sun, wind

or geothermal based technologies is not complementary. On the contrary, my costumer is

encouraged to invest money in other renewable technologies even if this project is studying a

system that would cover all his demand, because even if he produces more energy than the

part needed in the farm he could sell the electricity to external purchasers and act as a

generator - I reckon that one of the steps to be followed to cope with the global energetic crisis

mentioned before is to take advantage of all the valuable RES existing in every region locally,

even if they coincide with another activity that has nothing to do with generating electricity: This

would need to be accompanied with many regulatory changes and favourable frameworks.

Fig. 3.3 shows the overall impact of the different energy sources in the world in 2017, according

to the Global Status Report of REN21 of 2019.

Fig. 3.3. Estimated Renewable Share of Total Final Energy Consumption in 2017. (Source: [6]).


It is interesting to locate the magnitude of the production of electricity by using biogas if

compared to other RES. Actually, the most used source that is not a fossil fuel is the traditional

biomass (which is basically used for providing heat for space heating and cooking in poorest

countries). Then, in what REN21 calls “modern renewables” the main RES producing power

are listed (in descendent impact on the energy mix) as follows: Hydropower, wind, PV solar,

biomass geothermal and ocean power. Then, the use of methane produced by an anaerobic

digestion of residues don’t even have its own category in the power generation side. However,

biofuels for transport supposed in 2017 a 1% of the Total Final Energy Consumption of the

world but the use given to this products (biomethane, biodiesel…) is mainly for transportation

purposes [6]. From the data commented just now, it can be noticed that the impact of the

biofuels is considerably big if compared with many other RES. In this project the use of the

biogas – which in reality is biomethane, it is called indistinctly in this project in both ways since

biomethane is a type of biogas – is not related with transportation, and would be transformed

into electricity and heat.

Once all of this is clear, let’s introduce the EGS proposed in this project.

3.1. Objectives of the project

Firstly, there is the pure normative objective of the Master’s Final Thesis; since the

accomplishment of it is required for completing the Master’s degree in Energy Engineering.

Then, the main objective of the project is to carry out both technical and economic feasibility

analysis of an EGS that suits optimally to the thermal and electrical needs of the farm Can

Barrina:

• On the one hand, the technical study implies the dimensioning, designing and choosing

of the most convenient EGS (having all in common the part of the anaerobic digester).

In order to do this, it was required full access to all the data regarding the bills and

expenses of the farm from the energetic point of view. The mathematical and numerical

tools MATLAB and Excel are chosen to develop a mathematical model which allows

the calculation of the different energy balances taken into account for transforming the

residues of the farm into usable energy.

• On the other hand, the objective of the economic study is to find the amortization of the

investment taking into account the monetary savings produced after installing the EGS

and the initial cash outlay needed to install this system as well as the fixed and variable

costs that this would imply over the years. The tool Excel is used.

Another interesting objective is the calculation of the basic engineering costs of doing this

studio (which is estimated to demand for 600 hours).

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Finally, but no less important, there is the objective of doing an environmental analysis in order

to know which would be the impact of installing of this system in the real world. It consists in

comparison between the CO2 emissions related with a baseline case where no change in the

farm is proposed and another where the EGS described before is set up.

3.2. Area of application

Designing the optimal EGS based on the use of biomethane produced by transforming the

wastes of the farm requires a deep research in the existing technologies for doing the

conversion into biogas as well as for transforming this secondary energy source into usable

energy (following the definitions described in the Global Energy Assessment – Towards a

Sustainable Future [7]). Thereupon, the area of application of this project is limited to the mere

technical calculations needed to dimension and assess this system from a feasibility point of

view, requiring these steps:

• Deep analysis of the demands in Can Barrina as well as the fluctuations that may

have in different periods. This point is started by a description of the existing facilities

in the farm to make the reader

• Chemical analysis (basic) of the transformation of the wastes of the farm into raw

biogas. All the quantities of cattle raising and agricultural waste as well as the external

energy required in the biodigester must be known for calculating the generation rate

of biomethane.

• Technical - engineering - analysis of the different technologies that can be used for

transforming the biogas produced in the biodigester int final energy, and how can this

meet the demand of Can Barrina as well as with the added thermal demand (mainly,

even if there are some electrical components for sensoring) of the biodigester. The

research of technologies that can be compatible with the previous this step and the

previous one is also in the area of application of the project.

• Economic analysis of the installation to know its feasibility.

• Environmental analysis in order to know how installing this EGS would affect the

emissions of the farm to the atmosphere.

The area of application is delimited by the boundaries of what is necessary to carry out the

previous steps and what is not. In other words, any complementary information that is not

related with evaluating technically the proposed EGS is outside of the scope of this Master’s

Thesis.


4. Energy supply

A vital point to be studied in detail before even thinking on starting any kind of engineering

project is to assess the different characteristics of the client. In other words, it is crucial to

collect as much necessary data as it is possible to be able to perform a study suited and

optimized to the real needs of the client.

In this section - the first point of the central block of this project – it is analysed what defines

Can Barrina as a farm: Main activities carried out in the farm, existing facilities, basic thermal

and electrical loads, location, wastes or usable residues and so on. Let’s start then to describe

the farm itself and afterwards enter in detail with the demand.

4.1. Description of Can Barrina

Can Barrina is a familiar farm owned by the Vila family for more than 80 years (1940). The

origins of this farm were settled after the Spanish Civil War, when the grandfather of the current

owner, named Lluís Vila Ferrers, purchased the lands and started to breed pigs and cows. He

was one of 11 siblings and some of them started to work on the farm making it bigger year

after year. At certain point, the farm was inherited by the firstborn of Lluís; Joan Vila. Repeating

the history, the farm is now owned Joan’s son, Eduard Vila.

Can Barrina is located in the surrounding of Santa Cecília de Voltregà, Osona, province of

Barcelona. This small municipality has only 187 inhabitants right now, centre with a surface of

8,63 km2 in the old centre and its altitude from the sea level is 519 m [8]. The nearest

recognisable city is Vic, at 10,3 km from the farm [9]. Fig. 4.1 shows the landscape that can be

seen from the familiar house which is the core of the farm and where some members of the

Vila’s family are living today (house shown in Fig. 4.2).

Fig. 4.1. Can Barrina’s harvesting areas in front of the familiar house. (Source: Own).

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Fig. 4.2. Can Barrina’s domicile (Source: Own).

Focusing on the specific location of the farm, it can be found on the following coordinates:

• Latitude: 42º 00’ 09.7” (42,002699 º N)

• Longitude: 2º 13’ 17.4” (2,221489 º E)

To end with this brief introduction of the history of Can Barrina, it is interesting to show a real

image from satellite’s perspective of the farm and its surroundings, in order to ubicate it in the

real world (Fig. 4.3).

Fig. 4.3. View of the Can Barrina’s location from satellite’s perspective. (Source: [9])


4.1.1. Description of the activities developed

With the main objective of sustaining the business and profitability of the farm, the main

activities carried out are (explained and detailed by the farm’s owner):

1. Cow’s milk production: Can Barrina disposes – today that I am writing this, 25 of

February of 2020 (this day is taken into account also for the enumeration of pigs) - of

251 adult cows, from which 210 are used for milk extraction. The remaining ones are

used for reproduction purposes in their majority, having 60 calves (young bovines) at

this moment in a special cowshed (in Fig. 4.4 can be seen some of them).

Fig. 4.4. Most recent-born calves in Can Barrina (Source: Own).

The milk is not treated in the farm (in accordance with the sanitary regulatory

frameworks imposed by the EU), so is sold in its “natural form” directly to external

buyers in the wholesale market. Nevertheless, the final product that Can Barrina

presents an important difference if compared with the milk obtained by the direct

milking of the animal: It must be cooled down from 37 ºC (cow’s body temperature) to

4 ºC in a rapid refrigeration process. The reason of doing this is to preserve the

freshness of the milk and avoid some bacteria or processes dangerous for human

health. The method used for cooling down the milk is analysed deeply in the demand’s

analysis.

Finally, the milk at 4 ºC is stored in two thermally insulated tanks with refrigeration

which ensures its correct storage. These tanks are continuously emptied and filled out.

2. Pig breeding: Along with the milk production, the pig breeding supposes the other

main source of incomes of Can Barrina. This activity consists on the seasonal

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fecundation of 350 adult sows (pig female), that leads to a periodical pregnancy - the

pregnancy period lasts for 114 days in average. All the new born piglets (young pigs)

are sold to external purchasers as soon as the weaning is achieved successfully -

weaning is defined by Dictonary.com as “accustom (a child or young animal) to food

other than its mother’s milk; cause to lose the need to suckle or turn to the mother for

food” [10]. Fig. 4.5 shows one room of Can Barrina’s weaning house.

Fig. 4.5. Single room of Can Barrina’s weaning house. (Source: Own).

At this point, it seems interesting to explain briefly the life cycle of a pig, since the

existing demand associated to this activity relies on the phases performed in situ. Thus,

the main stages of a pig’s life cycle are:

- Pig farrowing: The first stage encompasses the birth of the animal until the day 27.

During these days it is compulsory to raise the pigs in a safe and protected habitat

with a mean ambient temperature around 21 ºC. The new-born babies would pass

this stage by drinking their mother’s milk.

- Weaning: The second stage comprises the period from the end of the 27 days of

pig farrowing until the animal is used to be self-dependent. It is an important stage

for the piglets since they would be put aside from their mothers. All the specialized

farms must ensure a minimum temperature of more or less 30 ºC that is usually

provided using thermal plates (heated up with electrical resistances, hot water or

burning fuels). This increment of temperature is the consequence of not having at

their disposal the body’s temperature of the adult sows.


- Fattening: The final stage of a pig’s life is the fattening, which suppose the largest

stage in terms of time (from the end of the weaning until their death). Usually,

excepting some bizarre cases, pigs are raised up with the objective of eating them

one day. Consequently, all their life is oriented to make them bigger and heavier

(or healthier if the quality of the meat is expected to be higher). In any case, the

fattening is not always carried out in the farm where the pigs are born because,

commonly, the pigs are fattened in the domains of who has a slaughterhouse at

their disposition. Another common model of farm is the one who grows the pig until

is big or old enough to be sold to external buyers.

In Can Barrina, pigs are sold to external buyers at the end of second stage (weaning),

and the fattening is done in other farms or facilities. All the costs associated to this

activity are recovered by selling the animals per unit and weight. In following points, it

would be detailed the demand associated to all of this.

3. Harvesting of wheat and corn: Another essential activity of the farm is the cultivation

of the 73,33 hectares (ha) of fertile land that Can Barrina has at its disposal (200

“quarters” in local units: 1 ha = 2,727397 “quarters”). All the cereals sown and collected

there are used for producing food exclusively for the adult cows (the young ones use

a different type of animal feed). Fig. 4.1 and Fig. 4.6 show a great part of the total

cultivation lands of the farm.

Fig. 4.6. Part of the cultivation lands existing in Can Barrina. (Source: Own).

The annual production varies from 850 to 3000 tonnes per year, with an approximate

average – according to the owner – of 2500 t (counting all the cereals and plants

cultivated in that field which are added to the food mix given to the cows). This variation

is clearly unusual, or at least of considerable magnitudes, and this happens because

only 8,18 % of the total land (6 ha) has irrigation at their disposal. Eduard Via and his

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father asked many times for an upgrading of the agricultural irrigation but the local

government denied the installation of new tubes and water channels systems since

there is not water enough in Catalunya for all the agricultural activities carried out in

that region. The solution taken by the family was to provide access to water in the most

fertile area – the mentioned 6 ha – to ensure a minimum production of at least 850 t,

even if the meteorological conditions of that year are severe.

The rest of the land doesn’t have access to water so the fluvial seasons and the year’s

meteorological conditions are essential to maintain the productivity in its optimal levels.

It can seem inconsequential to the final profitability (economical) balances of the year,

but a bad season can suppose monetary losses that are over 100.000 €. As a matter

of a fact, the effect of using part of the tillage for producing biogas must be analysed in

the economical balances of the feasibility of the EGS chosen in this project.

In the farm there are – mainly – two cultivation period which are:

• From autumn to spring: In this period both wheat and wins are cultivated

(among others such as barley or bagasse in smaller quantities).

• From spring to autumn: After some days of recovery of the fertility of the land,

maize is the cereal sown at the end of the spring to harvest it in autumn.

All this intensive agricultural activity takes place in an 85 % of all the land (obviously

the 6 ha with irrigation are included). The remaining 15 % of the fertile land is used for

pasture by the cows, which every day walk in that area. All the cereals are harvested

by a diesel collector- they rent it for just a couple of days - that crushes all the cereals

in tiny parts. This mix of crushed cereals (with other additives not cultivated in the farm,

that are bough to external companies) is then silty and stored in a silo where it ferments

for being transformed into bovines’ feed.

In order to maintain the land fertile all the year without requiring some gap years with

no cultivation at all, some natural fertilizers produced in the farm itself are used. These

fertilizers come from animal excrements (solid), animal slurry (liquid) and agricultural

wastes. The agricultural wastes along the solid cattle raising ferments in an aerobic

digester already existing in the farm, as it is detailed in the next and final main activity

carried out in the farm.

To sum up, all the agricultural activity is not destined to the selling of food to external


purchases, but it is essential to make the Can Barrina’s farm economically feasible due

to the high prices of the cows feed in the market - it is not specially expensive per unit

weight, but cows eat gigantic quantities of food: Approximately 26 kg/(day·cow)

according the farm’s owner.

4. Generation of fertilizers: The last main activity developed in the farm is the generation

of high-quality fertilizers which are sold to customers enrolled in the agricultural sector.

One of the most interested agents in purchasing these fertilizers are the winegrowers;

since vineyards require manure of high standards to potentiate the most-appreciated

characteristics of the grapes that will be used for producing wine.

In order to produce these fertilizers, the farm is using only the solid part of the

excrements of cows and pigs. There is a special machine in charge of cleaning the

barns of the adult pigs and cows (the separated animal shelters where piglets and

calves are staying are cleaned manually). Those machines work by dragging all the

cattle raising (solid and liquid) into a special channel where the liquid part is driven to

a storage pool and the solid part remains there – I prefer to not show the pictures I

took.

When the channels are starting to be obstructed, they must be cleaned and the solid

part is transported to a storage tank where Sun can start the dry up process. The overall

functioning is that the radiation coming from the Sun heat up this residue drying it up

at the same time. According to Eduard, they leave this part there until the aerobic

digesters mentioned in the previous activity have already worked properly with the

previous manure, generating the desired fertilizers. Once the aerobic digesters – there

are two – are emptied, new dried excrements are put inside the digester repeating the

process. Fig. 4.7 displays the mentioned digesters, which are undergrounded.

Fig. 4.7. Aerobic digesters for producing the high-quality fertilizers. (Source: Own).

Pág. 22 Report

And the obvious question here is: Why isn’t Can Barrina using these high-quality

fertilizers in their own fields?

This question can be answered in two basic points:

1. They don’t need these high-quality fertilizers for producing cereals destined

for producing food for the cows (there are more needed in other sectors).

2. It is part of the business, and they generate a significative income by selling

them to external buyers.

Besides, the slurry or liquid part cannot be taken out of the farm and each farm

(accordingly to the local legislation) must take care of that residues by themselves.

Many farm’s owner doesn’t want to use this part as fertilizers and neither keep it, since

it has lower quality, stinks, it is hard to spread it correctly in the field, it must be kept in

a special pool…

Actually, the EGS proposed in this project propose a solution to this problem since the

aerobic digester would work only with the liquid part of the cattle raising (it could work

with the solid one, but this project is going in favour of Can Barrina’s interests, and the

solid part is usable and provides income while the liquid one suppose a problem).

These are the main activities that the farm develops, and regarding the last paragraph of the

last activity – the paragraph just above – it is really interesting to understand why it would be

used the liquid and not the solid part of the excrements of cows and pigs. This assumption

would be considered for designing the anaerobic biodigester as well as in all the calculations

developed in this Thesis. In the following section there are analysed the existing facilities of

the farm (at least those which has a significative impact in the demand’s analysis).

4.1.2. Description of the existing facilities

The first point of interest to assess regarding the facilities of Can Barrina is the connections to

the basic mains and how they could affect to the EGS. Let’s see them:

• Electrical connection: The farm has access to the electrical grid (obviously), but the

peak power allowed to be used in the farm is equal to 43,3 kW. It can seem a large

number but for the most energy-intensive months of the year this limitation supposes

a problem and sometimes power outages occur. The farm has already payed for the

installation of a double line – undergrounded – with the intention of increase the


maximum power that it can get from the electrical grid. Nevertheless, the transformer

of the local electrical distributor (Endesa) needs to be replaced by a more powerful

model and this installation is still in process.

To face the risk of having insufficient power in punctual moments, the owners decided

to put PV solar panels by the end of this year. Despite this fact, this project only

considers the initial facilities of the farm and not the extensions or changes that would

be applied in the future. Focusing only in the current farm, it can be assumed that the

maximum power peak does not suppose a problem when assessing the EGS: Since

the outages occurs infrequently and the farm has already found measures to adapt the

electrical consumption to the existing limits.

• Natural gas grid supply: In Can Barrina, the connection to the natural gas (NG) grid is

inexistent. They asked to the local administrator access to this grip but being a rural

area and ubicated in a municipality so small as it is Santa Cecília de Voltregà, the

proposal has always been denied. For this reason, the familiar house - where there are

some people living in it – is equipped with butane (C4H10) cylinders for providing basic

needs such as space heating, gas for cooking or just Domestic Hot Water (DHW).

For other heating purposes needed in the activities mentioned before (specially cows’

and pigs’ breeding) the farm has two diesel-based boilers - vital since there’s not

access to the NG grid. The basic principles of this kind of engine are quite simple; a

fuel – in this case diesel – is burned and taking advantage of the energy released by

the fuel in the combustion reaction an increment of temperature is added to a flux of

water passing through the boiler in a countercurrent flow. Fig. 4.8 shows a scheme of

this kind of boiler. The demand associated to this lack of access to the NG grid is

considered in the section where the thermal demand is studied.

Pág. 24 Report

Fig. 4.8. Scheme of a typical diesel boiler. (Source: [11]).

• Water supply: Finally, another basic resource to be taken into account in a farm is the

water. Access to drinkable water is essential to:

o Give drink to the animals living in there; a single adult milk cow can drink from

38 to 110 L/day (more or less and 8-10 % of its weigh in water [12]) and a calf

about 5-6 L [13] – the 60 calves have at their disposal a 240 L tank which heats

water up to 37 ºC, since they need hot water in younger ages. Besides, adult

sows need approximately 7 L/day and piglets 1 L/day [14]. This leads to an

approximate daily consumption of 22354 L/day (using the mean values of daily

consumption for each animal).

o Irrigate the field ensuring boosting production (and increasing also the quality

of the grain or type of cereal).

o Cleaning the facilities; and specially the milking room where approximately

120-150 L of water must be heated up to 60 ºC (according the sanitary laws)

to clean the 16 milking extraction machines and all the milking room. Besides,

the cows’ and pigs’ barn and excrements extraction machines are periodically

cleaned.

o For spraying water over the cows every 25 seconds (according to Eduard)

when temperature exceeds 20 ºC in a special electric fan – cows must be all

the year in a specific optimal temperature threshold for their own health, since

they are really sensitive to high temperatures. Refrigeration of the cattle.

o Human water consumption needed in the familiar house.


The result is an extensive consumption of water, although as it was mentioned earlier,

the connection to the water grid is limited and is not enough for providing all the water

needed to irrigate all the land. A solution found by the owners was to construct a

deposit which recollect all the fluvial water coming from rains. This water stock is

specially needed in summer when water consumption is increased while the fans used

by cows are working.

Moving from the connection to the electrical, NG and water grid, a farm has many other

facilities and spaces destined to the activity. Fortunately, I had access to the farm’s project

where a design of all the farm is shown (see Annex I). An ampliation of the design presented

in the previously mentioned Annex is shown in Fig. 4.9 to see some of the most representative

blocks of the farm.

Fig. 4.9. Ampliation of the of the farm’s design showing the most important facilities. (Source: Own).

There are many important facilities, but I believe the naming of all of them is not necessary, so

the most significant ones are listed below:

• Rainwater accumulation reservoir mentioned previously, the gutters existing in the roof

of every single building (barn, stall or cowshed, familiar house, warehouse, familiar

Pág. 26 Report

house…) are canalized to a deposit destined to the irrigation.

• The main cowshed where all the cows are; it is equipped with three silos trench type

where the collected fodder are placed to feed the adult cows of the farm. This facility

is equipped with different levels (separating the part where food and water are served,

the sleeping zone, the “jazz room” where cows actually have classical music before

extracting the milk…), which are intercommunicated. Nevertheless, automatic doors

activated manually are used for separating the bovines from the milking and the jazz

room.

• The calves’ barn where there is a similar structure than the one presented in the main

cowshed but in a smaller scale (and without all the part of the milking and jazz room).

• The sows’ barn where the 350 adult pigs has at their disposition automatic feeding

machines that provide food in different ranges of time and individually to each sow.

Why do they eat individually? This happens because many sows of those living in Can

Barrina are pregnant. To be able to control their gestation period all the sows are

analysed each day using a chip and a small amount of blood analysed by an automatic

machine. The animals enter in a kind of narrow corridor where only one sow per time

can go in, and at the end the food is served. Nevertheless, to go out they must be

checked before and automatic door is opened. Eduard argued that the most dominant

sows are aggressive with the other ones generating a hierarchy and stablishing an

order. The sows that have already eaten are separated from the other ones by a metal

fence, which is opened once all the pigs have eaten (providing more space for the

animals.

• The pig farrowing house; here is where the sows give born to new babies and in six

separated rooms with 6 sows per room the mother with the recent born babies are put

in small parcels. Actually, a metallic structure is limiting the movements of the mother

only letting her to milk its children. This is done because in the past many piglets used

to die by being crushed by their mother by accident.

• The piglets’ weaning house is where all the young piglets of more than 27 days of life

are separated from their mothers and start to be independent before they are sold to

external buyers.

• There is a zone with some flat-plate solar collectors that helps to pre-heat the water

that goes inside the diesel boiler to produce DHW for cleaning purposes.

• All the liquid part of the excrements separated by the cleaning machine – and driven

through the special channel – are going to the slurry’s pool. Actually, the farm counts


with three pools but the vast majority of the slurry is sent to the pool number 3, which

is much bigger than the other two: Pool number 1 has 165,57 m3, pool number 2 has

101,31 m3 and pool number 3 has 1189,67 m3. Fig. 4.10 shows an image of 3rd pool.

Fig. 4.10. Slurry’s pool number 3 of great capacity. (Source: Own).

The total capacity reaches 2450,93 m3 as there are also the deviation channels, outer

pits and inner pits to be summed to the volume of the three pools. Besides, around 500

L/day of hot water coming from the cleaning rooms are thrown in pool number 3.

• The waste treatment area of solid excrements, which counts with a large storage facility

where it is dried and then the aerobic digesters already explained.

Let’s see now how all these elements are translated into energetic needs, entering in detail in

the engineering assessment expected from a Master’s Thesis.

4.2. Energetic loads associated to this activity

4.2.1. Cows’ associated loads

In this section the energetic loads associated to the cows’ breeding are exposed (without

entering in detail in the energy consumption during the year, what is done in following points).

One of the most energetically demanding devices used in this activity are the milk extraction

machines or just milking machines. Can Barrina counts with 16 milking machines (see Fig.

4.11) where the 210 cows used for obtaining milk pass three times per day (following the turns

displayed in Table 4.1). The electric motor used for running the 16 machines has 8 HP (Horse

Power), or 5,968 kW (remember that 1 HP = 746 W [15]).

Milking turns in a standard day

Turn 1: From 5:00 to 9:00 Turn 2: From 13:00 to 17:00 Turn 3: From 21:00 to 1:15

Table 4.1. Milking turns for the cows of Can Barrina in a standard day.

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It can be calculated easily how much time takes to milk one cow - considering that all of them

requires the same time what in reality is not exactly true - like follows in Eq. 4.1; as it is known

that the 210 cows pass into the 16 milking machines in 4 h (240 min). This leads to a mean

time (𝑡̅) for an extraction cycle of a single cow of 17,142 minutes (considering that all the cows

enter in the 16 machines in blocks of 16 cows at the same time).

𝑡̅ = ⌈(𝑁𝑐𝑜𝑤𝑠

𝑁𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑚𝑎𝑐ℎ

)−1

⌉ · 𝑡𝑡𝑜𝑡𝑎𝑙 = ⌈(210

16)

−1⌉ · 240 = 17,142

𝑚𝑖𝑛

𝑐𝑜𝑤 (Eq. 4.1)

The meaning of “⌈00⌉” is to round up to the nearest integer, since at the end 210 divided 16 is

not an integer value. In each complete milk extraction cycle is composed by 14 periods from

which 13 are using the 16 extraction machines and at the end only 2 cows remain alone in the

last extraction. All of this is interesting since the last 17,142 min the motor won’t work at full

load, and in a precise analysis as it is being developed this would suppose almost an hour

(51,426 min) of having the motor working at 12,5 % of its capacity.

When Eduard showed the farm for the second time with more detail, he demonstrated how he

put every time the suctioning part in charge of extracting the milk, and once it fits in the cow,

he pressed a button which starts the extraction of the milk of that specific nozzle (in total there

are therefore 16 nozzles). To simplify the further calculations, it is assumed that all the cows

are placed in their compartment at the same time and in blocks of 16 cows.

Fig. 4.11. Ten of the sixteen milk extraction machines (in off mode). (Source: Own).

Following with the analysis of the milk extraction, it has to be taken into account another energy

demanding point that is the cooling down of the milk’s temperature from 37 ºC to 4 ºC (for the

reasons already explained before). This process was supposed to be done directly in the

refrigeration tanks, but instead, they found a better solution which allowed them to have a


smaller motor inside the tanks and save energy; to have a plate heat exchanger liquid-liquid

type that produces a heat exchange with the extracted milk and the water existing in the

rainwater accumulation reservoir. Therefore, the milk is cooled down following 2 steps:

1. The milk goes from 37 ºC to 20 ºC using this plate heat exchanger. The energy

demand in this step fluctuates according to the temperature of the water along the year

(studied in the load flow studio). The basic principles of this heat exchange are simple,

the water (colder than the other fluid) extracts energy from the milk lowering down its

temperature in a countercurrent heat exchanger – analysed deeper in further points.

2. The milk goes from 20 ºC to 4 ºC in the refrigeration tanks using 2 motors of 5 HP

each (3,73 kW: A total of 7,46 kW) placed at the bottom of each tank (there are two

tanks, so one motor per tank). The motors are used to feed energetically a refrigeration

cycle with R-134a as refrigerant fluid and with all the components needed in this kind

of cycle: condenser, expansion valve, evaporator and compressor. An important detail

to take into account is that in hottest months if 20 ºC cannot be achieved at the entrance

of the tanks (since the temperature of the water of the reservoir is too high to achieve

20 ºC in the heat exchanger) more energy would be needed to be spent in the

refrigeration tanks. These fluctuations caused by the meteorological conditions are

also studied in the load flow studio.

Now, another crucial load which affects a lot in the monthly final electricity consumption is the

one composed by the group of 15 fans of 1 HP (0,746 kW) each that are activated when the

ambient temperature goes up to 20 ºC (Tamb ≥ 20 ºC) – supposing a total nominal power of

11,19 kW. When the fans are working, they also spread fresh water in form of water drops

every 25 seconds. Since the affectation is significant to the final electric bill, it makes a huge

difference in the hottest months (specially in summer) if compared to the other ones. Fig. 4.12

shows some of the cows and some fans; which try to mitigate the negative effects that could

appear in cows when this threshold temperature is exceeded (there are really sensitive).

Pág. 30 Report

Fig. 4.12. Main cowshed of Can Barrina; showing two of the exiting 15 fans. (Source: Own).

Some water needs mentioned before are listed again now (electricity is required):

- Breeding these cows demands cleaning the milking room (the 16 extraction

machines and the room) every time that the turn is finished – then, 3 times per day.

This means heating 120 – 150 L of water up to 60 ºC three times per day. This

water is heated up using an electrical resistance.

- The 16 calves have at their disposal the already mentioned tank with a capacity of

240 L of water that is heated up to 37 ºC with an electrical resistance.

There are other loads associated to the cows (automatic doors, lightning, pumps that

consumes electricity to transport water ad allows the heat exchange with the milk, speakers to

put classical music in the jazz room…) and so on. Nonetheless, these loads are neglected

since the impact in the final energetic consumption is not relevant if compared with the loads

recently mentioned. In summary, the main loads associated to the cows are:

• The 8 HP motor that runs the 16 milking extraction machines.

• The two 5 HP motors placed at the bottom of the two milk refrigeration tanks. The

electricity needed in the pumps of the plate heat exchanger can be neglected.

• The 15 fans of 1 HP each activated when Tamb ≥ 20 ºC.

• The electrical resistances to heat up water in both processes mentioned before.


4.2.2. Pigs’ associated loads

The main loads associated to the pigs breeding are those that supply thermal requirements of

this activity. In fact, in both the weaning rooms and the special space were pig farrowing occurs

the conditions in terms of temperature control are strictly regulated following the numbers

specified when this activity was presented. Just to refresh it, the 27 first days after the childbirth

the recent-born piglets are placed into a special location where 21 ºC must be kept constant.

In order to do this, 72 heating plates using hot water are used. In each of the 6 rooms there

are 12 plates, and the water is heated up thanks to a diesel/gasoil boiler. Despite that the

structure is thermally insulated, 15 heating pumps of 0,2 HP (149,2 W) each are used to ensure

the desired temperature (monitored constantly by thermostats). The plates are also important

for providing heat from the ground to the babies, and not simply space heating.

On the other hand, another important thermal consumption happens in the weaning room

where heating plates that goes up to 30 ºC must be put under the floor to provide the warm to

the piglets that their mother won’t provide anymore (since they are separated from the sow).

In this case there are 6 cabins – overcrowded with piglets – with 24 plates per cabin; having a

total of 144 plates. In this case they use electrical resistances of 100 W.

Finally, the automatic feeding machines suppose the last representative load regarding the

pigs breeding as well as all the monitoring system that control all the gestation period of the

sows. The motors used to open and close the automatic doors and to regulate the distribution

of animal feed cannot be quantified in power terms since Eduard didn’t know it exactly.

Nevertheless, in the next section the energy associated to these components is estimated –

we know that the automatic feeding machines work for 3h/day.

4.2.3. Agricultural and other loads

Regarding the energetic loads associated to the agricultural activities, the vast majority of it is

based in the diesel consumption:

• The tractor for moving things to one place to another, or to sow the land are diesel-

based tractors among many other uses.

• The rented diesel collector used to harvest al the cereals runs also with gasoil, so

there is not electricity consumption. Nevertheless, once this mix of cereals is crushed

and silted in the silo it needs some electricity while fermentation is going on the

preserve the quality of the food and a specific range of temperature.

• There are special kind of trucks used to transport the heaviest weights such as the

cows’ feed, the solid part of the manure and many other things, also diesel-based.

• Another representative vehicle is the one used for transporting the pigs, that is used

to bring them to the external buyers which pay for that animals. This trucks also use

Pág. 32 Report

diesel as fuel, and are not adapted to transport cows (cows are not on sale and in

theory they would stay in the farm excepting force majeure cases).

As it can be deducted, agricultural energetic consumption is in its majority based on moving

things, and using adapted vehicles to sow and harvest the land. Then, thermal energy is not

needed in any process since the plants are taking profit of the Sun’s radiation.

The last item that is analysed is the electricity consumption of the agricultural activities the

main loads associated to other activities (i.e. the production of fertilizers), and this is mainly

composed by:

• The pumps used to transport the water from the reservoir to the irrigation points.

• The sensors of rain and ambient temperature which are necessary to avoid

unnecessary consumptions.

• The machines that clean the cowshed and the barns of the pigs agglomerating all the

manure (liquid and solid part) in the already mentioned channel.

• The machines that separates the solid from the liquid part and rise up the solid part

that is collected and brought to the aerobic digesters.

• Lightning and luminaries in all the facilities and in some part of the field - since the main

access road to Can Barrina is well-illuminated (the activity starts very early each day).

• There is a 2-kW motor in the aerobic digester, which works 10 % of the time each day

(resulting in an average constant-consumption of 200 W) for producing the fertilizers.

• Many other loads that are not considered in detail in the load flow analysis; which are

included in the “other loads” group.

4.3. Load flow study

Fortunately, in this project I had access to the electric bills; and then the real demand can be

known (otherwise it would be impossible to know exactly the real demand without calculating

every single load and their specific working times). Annex II shows the specific electric bills

used to obtained the real consumption that was needed in the farm. This demand for a base

year considered as the standard one - obtaining the consumption by doing the mean values

between the monthly data acquired from the electric bills of 2018 and the ones of 2019 - is the

one that can be appreciated in Fig. 4.13.


Fig. 4.13. Monthly electricity consumption (kWh) of Can Barrina in the years 2018-2019. (Source:

Own).

From the electric bills of Annex II, it can be noticed that the months of May and July don’t

appear. In fact, there is data from July 2018 to April 2019 in the first electric bill and only data

from July 2019 to September 2019 in the second bill. This is because the farm changed of

distribution company in June 2019 (they moved from “Naturgy” to “Aldro Energia y Soluciones

S.L.”). For this reason, the last electric bill was not found by Eduard. In order to know the

demand of this months a simple solution was considered: Interpolating. A linear curve from

April 2019 to July 2019 (months with known data) was created with a slope (m) calculated

using Eq. 4.2 (where y2 is the electric consumption of the second month – July – y1 is the

electric consumption of the first month – April – and are the number of the month).

𝑚′ =𝑦2−𝑦1

𝑥2−𝑥1 (Eq. 4.2)

In this way, x2 and x1 are 7 and 4 respectively, and the demand of May (x = 5) and June (x =

6) can be calculated following the equation of the line shown in Eq. 4.3.

𝐸𝑐𝑜𝑛𝑠(𝑥) = 𝑦1 + 𝑚′ · (𝑥 − 𝑥1) (Eq. 4.3)

The results of that estimation were commented with Eduard and he said that they can be

considered as valid results; since the month with higher electrical demand are always July and

August, and the slope is quite linear. Obviously, the electric demand is much higher in hotter

months but, on contrary, the thermal demand is higher at colder ones.

Another problem found in just analysing the electric bills (which gives only the consumption at

the end of the month) is that the hourly demand cannot be known. As a matter of a fact,

knowing the demand hourly would help to make the sizing of the EGS better since the days

0

5000

10000

15000

20000

25000

Electricity consumption 2018-2019 (kWh)

Pág. 34 Report

with maximum demand could be found.

For this reason, the solution adopted in this project is to consider the hourly demand of the

most important devices in terms of electricity consumption and analyse their hourly demand.

This can be known easily since some of them are fixed loads that work identically every day

of the year (milking machines, electrical resistances for the piglets…) and some of them

depends directly on the meteorological conditions (fans for cows, milk refrigeration tanks…).

To adapt all this consumption with the overall one, a simple and effective approach has been

proposed: To divide all the loads that are included in the “other” group (since are not the most

representative ones) and consider that their consumption is distributed homogenously along

each specific month.

To illustrate better this idea, the total monthly consumption (Ei) is composed in Eq. 4.4 as the

sum of the energy required by the main devices (Mi) and the energy required by the other loads

(Oi); for the month “i”.

𝐸𝑖 = 𝑀𝑖 + 𝑂𝑖 (Eq. 4.4)

Before detailing the hourly electrical demand along the year, it is essential to know how the

external atmospheric conditions would affect in the thermal and electrical demand. Some of

the main loads that composes Mi are completely dependent on the ambient conditions.

4.3.1. Dependence on meteorological conditions

In Can Barrina, there are many machines and equipment that only work in a specific range of

meteorological conditions (as it has been listed in the previous section). Some of them can be

negligible since their impact in the final energetic consumption of the farm is anecdotic

(radiators and air conditioning of the familiar house, lightning that is more used in winter…),

whereas some devices really counts in the deviation of the overall electrical demand

depending on the month of the year (fans for cows, thermal resistances…). Hence, the

variation between the monthly final electrical requirements appreciated in Fig. 4.13 appeared

due to the environment fluctuation conditions.

Besides, in following sections the impact of the ambient temperature in the energy losses of

the system of our EGS becomes crucial (especially in the biogas anaerobic biodigester, which

has losses into the environment and a deep analysis of that losses is essential to asses is

performance and develop an optimal sizing). For this reason, in this section a modelling of the

meteorological conditions in Santa Cecília de Voltregà is carried out. With the results of this

analysis the operation conditions of the cows’ fans would be rapidly determined in the next


section (4.3.2. Electrical demand) as well as other thermal loads (which some use also

electricity).

To do it, the first step consist in finding out all the temperatures every hour in the location of

the farm. Actually, Can Barrina counts with some sensors in different rooms and places in the

farm to regulate some loads which are temperature dependant, but unfortunately, we were not

able to find a register of all this data (the devices actuate immediately and don’t record or

monitor the data collected). However, there are some websites that allow the obtaining of this

data. In particular, in this project PVGIS was used for obtaining the hourly temperature in the

farm’s location, like it can be seen in Fig. 4.14. [16]

Fig. 4.14. PVGIS interactive tool, meterological conditions in Can Barrina. (Source: [16]).

This tool is really interesting because it uses different weather stations and formulas to

interpolate the expected temperature in a specific location according to the geography, altitude,

presence of water…resulting in a good way to standardize a variable parameter as it is

temperature. As it can be appreciated in Fig. 4.14, the selected period of historical data from

2005 to 2014 was simulated and the results, using this period as example, are the ones that

can be observed in Fig. 4.15.

Pág. 36 Report

Fig. 4.15. Typical meteorological year: Dry bulb temperature according to PVGIS in the standard year

calculated with the mean values from 2005 to 2014. (Source: [16])

At the end, in this project the period of historical data used is the one that goes from 2007 to

2016 generating a standard year with the temperatures occurred in that period. This choice is

due to a basic principle of using always the newest data as possible. Another option that it was

considered was to generate this standard year with the data collected from 2004 to 2020 in

the meteorological station of Vic (information available in meteo.cat, [17]), but it was discarded

since the location is not the same, and this could generate some inaccuracies.

In the next section it would be explained how temperatures are used to calculate the electrical

demands, but right now it seems interesting to analyse a bit the temperature fluctuation along

the year. To do so in a visual way, it was decided to calculate the hourly mean temperature for

each month (𝑇ℎ,𝑖̅̅ ̅̅ ) of the year using a very simple calculation: The summation of all the

temperatures at the hour “h” for the month “i” divided the number of days of that month (di);

see Eq. 4.5.

𝑇ℎ.𝑖̅̅ ̅̅ ̅ =

(∑ 𝑇𝑖,𝑑,ℎ𝑑𝑖𝑑=1

)

𝑑𝑖 (Eq. 4.5)

From the previous equation it is interesting to see that the auxiliary value “d” would generate a

number of sums from 1 to the number of days of the months “di” for each specific hour (out of


24 h that a day has). In example, if it is desired to find the mean value of the temperatures at

9:00 p.m. (h = 21) in the month of October (i = 10; di = 31 days) the calculation would be:

𝑇21,10̅̅ ̅̅ ̅̅ ̅ =

(∑ 𝑇10,𝑑,2931𝑑=1 )

31=

𝑇10,1,21 + 𝑇10,2,21 … 𝑇10,31,21

31=

(12,8 + 13,3 … 9,3) [º𝐶]

31= 14,05 º𝐶

Once this is done, all the mean temperatures for each specific hour for each month of the

standard year (𝑇ℎ,𝑖̅̅ ̅̅ ) can be obtained; and they are displayed in Table 4.2.

Table of mean hourly temperatures (ºC)

Hour: Jan. Feb. March Apr. May June July Aug. Sep. Oct. Nov. Dec.

1 3,68 4,42 5,87 7,98 11,20 12,33 15,39 15,83 14,67 11,78 6,81 4,23

2 3,26 3,84 5,23 7,25 10,53 11,50 14,53 14,94 13,97 11,20 6,32 3,80

3 2,86 3,28 4,59 6,55 9,85 10,67 13,64 14,06 13,25 10,61 5,83 3,37

4 2,44 2,71 3,95 5,82 9,17 9,85 12,77 13,18 12,56 10,00 5,33 2,95

5 2,02 2,14 3,30 5,11 8,49 9,04 11,90 12,29 11,85 9,39 4,84 2,53

6 1,60 1,58 2,65 5,09 9,52 10,99 13,52 12,97 11,19 8,79 4,35 2,10

7 1,18 1,06 3,73 6,75 11,07 12,71 15,08 14,54 12,79 8,75 3,87 1,68

8 1,91 3,44 5,46 8,43 12,70 14,50 16,92 16,52 14,42 10,80 4,94 1,88

9 3,50 5,63 7,47 10,17 14,20 16,18 18,85 18,45 16,24 12,68 6,47 3,34

10 5,09 7,15 9,17 11,68 15,50 17,78 20,66 20,39 18,02 14,50 8,19 4,98

11 6,55 8,65 10,77 12,94 16,70 19,16 22,30 22,18 19,80 16,14 9,69 6,49

12 7,67 9,91 12,01 14,02 17,69 20,20 23,57 23,58 21,08 17,47 10,94 7,73

13 8,36 10,79 12,96 14,83 18,45 21,03 24,57 24,55 21,87 18,29 11,89 8,64

14 8,57 11,37 13,42 15,35 19,08 21,47 25,20 25,22 22,31 18,68 12,27 9,05

15 8,38 11,28 13,50 15,43 19,39 21,70 25,42 25,46 22,32 18,62 12,23 8,91

16 7,62 10,49 13,05 15,21 19,26 21,50 25,22 25,30 21,95 18,04 11,50 8,19

17 6,58 9,15 12,06 14,52 18,71 20,89 24,56 24,53 21,06 16,91 10,31 7,06

18 6,21 8,50 10,73 13,45 17,85 19,85 23,45 23,29 19,74 15,94 9,88 6,71

19 5,84 7,91 10,04 12,43 16,67 18,54 22,02 21,84 18,98 15,32 9,43 6,36

20 5,48 7,31 9,35 11,63 15,76 17,44 20,90 20,81 18,23 14,68 8,99 6,02

21 5,12 6,73 8,66 10,84 14,85 16,34 19,79 19,78 17,46 14,05 8,55 5,65

22 4,75 6,13 7,97 10,06 13,95 15,25 18,66 18,75 16,70 13,42 8,11 5,31

23 4,38 5,54 7,28 9,26 13,03 14,15 17,55 17,72 15,93 12,80 7,66 4,95

24 4,02 4,94 6,61 8,47 12,14 13,06 16,42 16,68 15,13 12,16 7,23 4,60

Table 4.2. Mean hourly temperature (0:00 – 23:59) for each month; for standard year. (Source: Own).

In Table 4.2 there are some mean temperatures that have been underlined in salmon colour

(red/pink); and this has been done to exemplify the importance of considering the effect of

temperature in some loads such as the fans for cows. In this case, it can be appreciated that

in that intervals of time from June to September it is likely that the fans are working

independently of the day (since the average is above 20 ºC). Nevertheless, this does not mean

that they are working every day: Some days are hotter or colder than others, so assuming that

Pág. 38 Report

all the days of the month work identically it would lead to results deviated from the reality;

specially since many hours with the mean value below 20 ºC would exceed this threshold

temperature in specific days.

The solution is presented in next section, and consist in analysing the electric and thermal

loads hourly (not with the mean values, but with the real values of the 8760 hours of the year

individually). However, Table 4.2 is expected to be used as a reference by the reader, since

presenting all the temperatures like it has been done in Fig. 4.15 may be confusing.

4.3.2. Electrical demand

In this section the overall electrical demand of Can Barrina is approximated hourly. The main

electrical loads (Mi) are analysed while the other loads (Oi) are estimated to follow the total

monthly demand (Ei) as it was described in Fig. 4.13, making an important assumption:

• From Fig. 4.13 the total consumption for each month is known and the Oi are

distributed homogeneously over all the hours of that month.

The chosen way to proceed is to analyse first the main electrical loads one by one and present

the sum at the end of this section:

Load 1) Fans for cows:

This load is particular because its consumption can go from zero in some periods of the year

or to high consumption values in other ones. After collecting all the climate data for the farm’s

location it was immediately calculated which hours the fans would work in the standard year

and which hours this devices would be stopped – depending on the ambient temperature

(Tamb), if is higher than 20 ºC the fans would start to work (for the reasons already explained).

A Boolean value “B” (1 or 0) is associated to each hour with a simple “if” function, and then the

electrical demand for these fans for each hour of the year is calculated following Eq. 4.6.

𝑃𝐹𝑎𝑛𝑚,𝑑,ℎ = 𝑃𝐹𝑎𝑛𝑛𝑜𝑚 · 𝑁𝑓𝑎𝑛𝑠 · 𝐵𝑚,𝑑,ℎ (Eq. 4.6)

Where:

• PFannom is the nominal power of each fan (1 HP)

• Nfans is the number of fans

• Bm,d,h is the Boolean value found that indicates if the fans are working (1) or not (0) in

the month “m”, day “d” and hour “h”.


• PFanm,d,h is the electricity consumption in that specific hour of the year (“m”,”d”,”h”).

Fig. 4.16 shows the total electricity consumption associated to the fans over the year for each

hour.

Fig. 4.16. Total energy consumption of the fans for each hour of the standard year. (Source: Own).

As it can be appreciated in Fig. 4.16, the vast majority of the consumption associated to the

cows’ fans happens in the summer month. To visualize this fact clearer, Fig. 4.17 shows the

working hours of the fans for each month of the year.

Fig. 4.17. Working hours of the fans per month over a standard year. (Source:Own).

Multiplying the working hours shown in Fig. 4.17 by the nominal power of the 15 fans it can be

obtained the total consumption per month that would be added to Fig. 4.28. The total energy

consumption associated to the fans in one year is equal to 14088,21 kWh (April: 190,23 kWh;

May: 1309,23 kWh; June: 2036,58 kWh; July: 3838,17 kWh; August: 3771,03 kWh;

September: 2383,47 kWh and October: 559,5 kWh). A graphic of the electricity consumption

0 0 0 17

117

182

343 337

213

50 0 0

Monthly working hours of the fans: Standard year

Pág. 40 Report

of the fans for each month would have the same equal shape - but different values - than the

previous one made for the distribution of the working hours.

Load 2) Milk extraction machines:

Calculate the consumption of the milk extraction machines is trivial, since the time that the

machine is working at its nominal power, when it is stopped and when is working at partial

load. Besides, it can be assumed that the consumption is identical every day and occurs in the

same way at the same specific time. Remember that Table 4.1 shows the milking turns for the

210 cows used for this purpose. The results obtained by using Eq. 4.1 were a milking time for

each cow equal to 17,142 min: The first 208 cows use the machine in groups of 16 using the

nominal power of the milking machines, and in the last turn the remaining 2 cows are milked

using only a 12,5 % of its capacity.

To calculate the electricity associated to this each hour, we just need to multiply the power at

which the machine is working (Pmilk) per the working time (tw). However, the 17,142 min

associated to each cow didn’t consider the time that takes to put the nozzle around the cows’

udder (breasts) and then remove it – as well as the necessary time to move the cows from one

place to another. According to Eduard this time can be assumed to be 2 minutes per cow,

having a milking time of 15 minutes (which facilities the calculations).

Following this assumption, calculating the working time in each period of one hour is interesting

to determine the hourly consumption for the standard year in Can Barrina, and the calculation

of each working time has been done in Table 4.3. Only the last working time has a variation in

the power used by the milking machine, so the calculation has been done in [Wmin] to take

into account the minutes at which the machine is working at nominal power (Pnom) and those

at partial load.

In Table 4.3 every 60 minutes are divided in time wasted for moving the cows and putting them

in each nozzle (red colour), those at which the machine is working (green) and in the last hour

the minutes with no activity at all (blue) – due to the approximation made where 17,142 min

minus 2 min would are only 15 minutes of useful work. The electricity consumption in kWh for

each hour is also presented at the end of the table. Is important to understand why only the

last 15 minutes at which the machine is working work at 12,5 % of Pnom.

Period 1st hour 2nd hour 3rd hour 4th hour

Calculation 60 = 2 + 15 + 2 +15 60 = (15-7) + 2 + 15 60 = (2-1) + 15 + 2 + 60 = (15-8) + 2 + 15 +


of working

time

+2+15+2+7

tW1 = 15+15+15+7

+2+15+2+ 15 +1

tW2 = 8+15+15+15

15+2+ 15 +2+8

tW3 = 15+15+15+8

2 +15 +2 + 15 + 2

tW4 = 7+15+15+15

tW (min) 52 min at Pnom 53 min at Pnom 53 min at Pnom 37 min at Pnom and 15

min at 12,5% of Pnom

Econs (kWh) 5,172 5,272 5,272 3,681

Table 4.3. Calculation of the energetic demand (kWh) for each milking period. (Source: Own).

To make the results more visual, Fig. 4.18 shows the evolution of the electricity consumption

(Econs) for one day. Remember that the consumption was assumed to by the same for all the

days of the year for this specific load.

Fig. 4.18. Electrical consumption of the milking extraction machines for a standard day (kWh).

(Source: Own).

Load 3) Milk refrigeration tanks:

In this step the electrical consumption associated to the process of cooling down the milk from

37 ºC to 4 ºC is studied, as well as the energy wasted in order to maintain that temperature

inside the two tanks. The amount of energy needed relies in the meteorological conditions,

since at higher temperature rates there are more losses in the tank; losses that are going to

be calculated in this section in order to have a complete hourly distribution chart of the tank’s

demand.

There is a thing needed to be taken into account and it is the volume of milk entering to the

tanks each days and which portion represents to the total capacity of the tanks. The two tanks

0,000

1,000

2,000

3,000

4,000

5,000

6,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ele

ctri

city

co

nsu

med

(kW

h)

Hour of the day (h)

Electrical consumtpion per hour in standard day

Pág. 42 Report

have a total capacity of 7500 L each (15000 L in total). According to Eduard the mean milk

production from a cow in this farm goes around 26 L/day. Since they’re milked 3 times per day,

this means 8,67 L per milking period and cow. With 210 cows, it can be approximated that in

each of the three turns 1820 L of milk would enter to the tanks (supposing 5460 L/day in total).

The tanks are filled up in turns, first one is filled up and when is full the other one starts the

filling period. From this, three very important assumption are made and they would be crucial

this would be crucial to understand the final results:

1. When the milking machines are working (210 min distributed in 4 hours like described

in Table 4.3) all the milk is entering to the refrigeration tanks after passing through the

plate heat exchanger – the one explained before that lowers down the temperature

from 37 ºC to 20 ºC. During that time the only one of the two motors would work, since

they’re not filled up at the same time (first one, once is full the other). Besides, each

motor would work the half of time at its nominal power since the plate reduce the energy

needed to refrigerate the milk inside both tanks in that order of magnitude, following

also the recommendations described in the article [18] for a similar system. However,

the power delivered by the water pumps that feed the plate heat exchanger is summed

in that periods that the milking machines are working.

2. Once all the milk has entered, is immediately cooled down to 4 ºC and the only needed

consumption is the one necessary to keep that temperature inside the tanks.

Therefore, the energy losses (described in this section) are the only consumption while

new milk is not entering to the tanks.

3. It would be approximated that the motors work identically independently of the tank’s

level. Obviously, if the tank is full of already cooled milk the new milk would transmit by

conduction temperature to the coldest one. Besides, this milk would be heated up and

the motors would be required to work. For this reason, to not enter in complicated non

steady-state analysis (which is out of the scope of the calculation of the demand since

the variation won’t be significant) this assumption is accepted.

Let’s see now how the total hourly demand for the standard year is calculated. With assumption

1 the demand for the 12 hours per day that the cows are milked is known; (2,865 kWh) each

hour: 1,865 kWh are used for the 5 HP motors located at the bottom of one tank and 1 kWh

goes for the pumps used for the initial heat exchange. However, without that plate heat

exchanger the consumption in one of these hours would be equal to 3,73 kWh, supposing

savings of 23 %.


Fig. 4.19. Milk refrigeration tanks of Can Barrina. (Source: Own).

Taking into account assumption 2, the losses of the tank must be determined. Fortunately, the

tanks’ main parameters were known by the farms’ owners, being the most important ones (Fig.

4.19 shows the refrigeration tanks):

• r1 = 0,9 m; r2 = 0,95 m; r3 = 0,98 m (see Fig. 4.20 a)). The internal cylinder of radius

“r1” describes de volume that can be filled up with milk. Between “r1” and “r2” there is a

crystal fibre with low thermal conductivity (kf = 0,04 W/(m·K)) of a width equal to 5 cm

(r2 -r1). Finally, there is a 3 cm protection of stainless steel AISI 316 (ks = 13,4 W/(m·K)).

• The altitude of the tank is equal to 3 m (L = 3 m), the volume of the tank with that data

would be around 9 m3 following this parameters (Vt = π·r12·L) but half meter is not

counted as storage volume since is in the bottom of the tank the motor, electronic

systems and the extraction/filling up systems are located. The useful capacity is then

7500 L.

Knowing the geometrical distribution of the insulation materials, the inlet temperature of the

milk (considered constant, which in periods of non-milk production is Ti = 4 ºC) and the outside

temperature (Tamb) of each hour; the total losses due to non-perfect insulation of the tanks can

be calculated. Besides, another needed parameter is the wind speed (vwind), because to

calculate the power loses accurately the convection heat transfer coefficient (h) is also

calculated. Let’s see then the mathematical expressions used.

To calculate the power losses, it must be known first the total thermal resistance (Rtot)

presented by the thermally insulated – but not perfectly insulated – milk refrigeration tanks.

Once “Rtot” is known, the heat transfer rate (qr) between the milk and the ambient temperature

Pág. 44 Report

would be equal to the losses, following Eq. 4.7 [19].

𝑞𝑟 =𝑇𝑎𝑚𝑏−𝑇𝑖

𝑅𝑡𝑜𝑡 [𝑊] (Eq. 4.7)

The equivalent thermal circuit of both tanks is identical and it is represented in Fig. 4.20 b), as

well as a basic design of a horizontal section of the tank from any point of the cylinder (showing

the radius and materials).

Fig. 4.20. a) Horizontal section of a milk refrigeration tank. b) Equivalent thermal circuit for the tank.

(Source: Own).

The formula used to find “Rtot” is Eq. 4.8, where the parameter “h” is calculated taken into

account the wind speed and the outside temperature for each hour like it is now justified. Firstly,

it is needed to find the properties of the air at each specific temperature for each hour of the

standard year; and they are found following the values already used in previous sections [16]

and then using tables of air properties found in the book “Fundamentals of Heat and Mass

Transfer” [19]. Then, with this properties and the velocity of the wind for each hours of the

standard year (also available when downloading the temperatures in [16]) the Reynolds

number (Re) is calculated as shows Eq. 4.9. Once “Re” is found the Nusselt number (Nu) is

calculated following Eq.4.10, that takes into account if it’s a laminar or a turbulent flow and the

magnitude of the previously calculated Reynolds number. Finally, the convection heat transfer

coefficient “h” is calculated is it is seen in Eq. 4.11. [19]

𝑅𝑡𝑜𝑡 = 𝑅𝑐𝑜𝑛𝑑1 + 𝑅𝑐𝑜𝑛𝑑2 + 𝑅𝑐𝑜𝑛𝑣 = 𝑙𝑛(

𝑟2𝑟1

)

2𝜋𝑘𝑓𝐿+

𝑙𝑛(𝑟3𝑟2

)

2𝜋𝑘𝑠𝐿+

1

2𝜋𝑟4𝐿ℎ [

𝐾·𝑚2

𝑊] (Eq. 4.8)

𝑅𝑒 = 𝜌·𝑉𝑤𝑖𝑛𝑑·𝐿

𝜇 (Eq. 4.9)


𝑁𝑢 = 0,027 · 𝑅𝑒0,805 · 𝑃𝑟1

3 (Eq. 4.10)

ℎ =𝑁𝑢·𝑘𝑎𝑖𝑟

𝐿 (Eq. 4.11)

Where:

• The parameters μ, Pr, ρ and kair are the values obtained from the air tables mentioned

before at each specific temperature.

• The Nusselt number is always assumed for Reynolds number >40·105, since the

variation of the convection heat transfer coefficient would be very little anyway from the

real values. This happens since at low wind velocities the Reynold number is smaller

and then “Nu” decreases following 𝑁𝑢=0,027·𝑅𝑒0,805 · 𝑃𝑟1

3

(, provoking a smaller “h” that would be really similar to the one obtained if every

Nusselt calculation is adapted depending on the Reynolds number [19].

Once all of this is done, Eq. 4.7 is applied so the thermal losses con be known multiplying the

heat transfer rate “qr” (W) by the time (always a period of 1 h). To visualize the results, it was

decided to compare the consumption for the coldest day of the year and for the hottest one. In

this way, considering that the motors work identically in both days while milk is entering to the

tanks (following assumption 1 of this section) a comparison of the affectation of the thermal

losses can be made. After searching the minimum and maximum temperatures, it was found

out that 14th of February is the coldest day – with a minimum temperature equal to -5,1 ºC –

and 29th of July is the hottest one – with a maximum temperature of 31,1 ºC). Fig. 4.21 and

Fig. 4.22 show the Electricity consumption (Econs) for both days, respectively.

Fig. 4.21. Calculated refrigerator tanks’ electricity consumption on 14th February. (Source: Own).

0

0,5

1

1,5

2

2,5

3

3,5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Eco

ns

(kW

h)

t (h)

Econs refrigeration tanks the 14th February of standard year

Pág. 46 Report

Fig. 4.22. Calculated refrigerator tanks’ electricity consumption on 29th July. (Source: Own).

It is interesting to see that the thermal insolation works quite well, since the thermal losses

won’t make a huge difference between the coldest and the hottest days in terms of final energy

consumption (34,38 kWh for 14th February against 40,032 kWh for 29th July). As it can be seen

in Fig. 4.21 there are no losses in the tanks for the 14th February, and this happens because

the ambient temperature is lower than the milk’s temperature stored in the tank during the 24

hours of that day (Tamb < Ti). Therefore, instead of entering heat into the tanks the energy is

being released from the milk to the exterior, becoming colder.

Obviously, since the thermal insulation mainly performed by the 5 cm layer of glass fibre with

low “k” generates a very good insulation in summer in return we cannot take advantage of the

cold temperatures in winter to reduce the energetic needs during that period (at least not in a

significant way). The losses in Fig. 4.22 suppose a 16,44 % of extra energy usage to cover the

thermal losses experienced by the tank in a really hot day. It is actually the maximum it can be

expected.

Another important detail is the small influence of the air convection effect if compared to the

impact that the ambient temperature has. Fig. 4.23 shows the wind speed for the two days

analysed before, and it can be seen that actually in 14th February the wind speed was clearly

higher than in 29th July. Nevertheless, analysing days with high wind velocities and warm

temperatures it was seen that the final energy consumption is smaller than the one existing for

the day with maximum temperature, confirming the initial statement announced in this

paragraph.

0

0,5

1

1,5

2

2,5

3

3,5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Eco

ns

(kW

h)

t (h)

Econs refrigeration tanks the 29th July of standard year


Fig. 4.23. Wind velocities for 14th February and 29th of July of the standard year. (Source: Own).

All the hourly consumptions associated to the refrigeration tanks are summed to the total Fig.

4.28, and the next electrical load analysed are the electric resistances.

Load 4) Electrical resistances for heating water:

In this section, two different loads are analysed using the same mathematical calculations but

culminating in different results. These loads are:

a) 150 L of water heated up to 60 ºC to clean the milking machine and the room every

time that this machine is used (three times per day), the heating happens during the

last hour of every milking period – like this they can clean immediately.

b) 240 L of water heated up to 37 ºC for the calves one time per day. In this case it can

be assumed that the consumption is distributed constantly along each day.

To calculate the demand, it is important to know which is the average temperature from the

water coming from the grid or from the reservoir. This data was found for the city of Barcelona

and Girona, being really similar in both cities [20]. Actually, Vic is closer to Girona and the

meteorological conditions are really similar. Assuming that the temperature of the water

coming from the grid and the one coming from the reservoir is the same, Table 4.4 shows the

values used in the calculations for each month.

0

2

4

6

8

10

12

14

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Vw

ind

(m

/s)

t (h)

Wind speed 14th February and 29th July

29th July 14th February

Pág. 48 Report

Mean water grid temperature for each month

January February March April May June

8 ºC 9 ºC 10 ºC 11 ºC 14 ºC 16 ºC

July August September October November December

19 ºC 18 ºC 17 ºC 14 ºC 10 ºC 9 ºC

Table 4.4. Mean approximated water temperature for each month in Can Barrina. (Source: Own).

In this case the mathematical expression to be used for calculating the electricity consumption

is really easy. First, the thermal demand (Eth) is calculated and then a efficiency (η) of 99 % for

the electrical resistance is assumed following the typical efficiencies for different electrical

resistances for industry found at the catalogue of the company BrotoTermic “Resistencias

Eléctricas Calefactoras” [21]. In order to calculate the thermal demand it was just required to

know the mass (m) of water that is needed to heat up – in case a) 150 kg and in case b) 240

kg of water; assuming that 1L = 1 kg – and the increment of temperature of it, since the specific

heat is already known for water at atmospheric pressure (Cp = 4180 J/(kg·K), approximated

according [19]).

Eq. 4.12 shows how it was calculated the thermal demand considering that “Tf” is the final

temperature that is desired to obtain – 60 ºC for case a) and 37 ºC for b) – and that “Tgrid” is

the temperature of the grid’s water for each month (according to Table 4.4). Besides, the

electrical demand is obtained following Eq. 4.13 with an efficiency of 99 %.

𝐸𝑡ℎ = 𝑚 · 𝐶𝑝 · (𝑇𝑓 − 𝑇𝑔𝑟𝑖𝑑)[𝐽] → [𝑘𝑊ℎ] (Eq. 4.12)

𝐸𝑐𝑜𝑛𝑠 = 𝐸𝑡ℎ/𝜂 (Eq. 4.13)

For load a) the water is heated up during the last hour of every milking process – so three

times per day – while for load b) the water is heated up constantly over the day. Fig. 4.24

shows the electrical consumption for this purpose for the 1st of January. On the other hand,

Fig. 4.25 shows the total consumption for both cases along the year (it can be noticed how the

temperature of the water of the grid/reservoir would affect to the electrical consumption

depending on the month). Clearly, the energetic demand in colder months would be higher; as

it is the increment of temperature too.


Fig. 4.24. Electricity consumption for case a) and case b) the 1st of January of the standard year.

(Source: Own)

Fig. 4.25. Hourly electrical demand of the electrical resistances for the standard year; cases a) and b).

(Source: Own).

It is actually impossible to appreciate this; but in Fig. 4.25 the demand for load a) is almost all

the time 0 except three hours per day (when the milking room is cleaned). On the other hand,

the demand for load b) is constant all the hours of each month but variate depending on the

0

1

2

3

4

5

6

7

8

9

10

-1 4 9 14 19 24

Eco

ns

(kW

h)

t (h)

Electricity consumption in electrical resistances the 1st of January

load a)

load b)

-2

0

2

4

6

8

10

0 1000 2000 3000 4000 5000 6000 7000 8000

Eco

ns

(kW

h)

t (h)

Hourly electrical resistances' demand along the year

load a)

load b)

Pág. 50 Report

month. In all of this analysis the only parameter that changes are the temperature of the water

coming from the grid or from the reservoir. To visualize clearer the difference between months

Fig. 4.26 shows the electrical demand for both loads one day of February (let’s say the 1st, but

they’re all identical) and one day of July (the 1st again).

Fig. 4.26. Electrical demand for the 1st of February and 1st of July of the electrical resistances.

(Source: Own).

Load 5) Heating plates for pigs:

This load is the simpler one to calculate, since it is composed by the 144 heating plates of 100

W each installed in the weaning room; where they have to produce a constant temperature of

30 ºC to ensure the adequate conditions for the piglets during this sensitive stage of their

developing. There are 6 cabins (or rooms) in the weaning room (or weaning house), and 24

small plates per cabin. To maintain 30 ºC each plate is regulated to work at maximum power

only 10 % of the time or at 10 % of their nominal power constantly.

Since their consumption is identical for each day, hour and second of the year it can be

assumed that they give 10 W/plate constantly along the year – knowing that the demand would

be equal to the 10 % of the worst possible scenario where they work maximum power all the

year. Since there are 144 plates; the total demand for the plates is equal to 1,44 kWh per hour.

This leads to a daily consumption of 34,56 kWh, and a monthly consumption of:

0

1

2

3

4

5

6

7

8

9

10

-1 4 9 14 19 24

Eco

ns

(kW

h)

t (h)

Econs of electrical resistances the 1st of February & July

load a) February

load b) February

load a) July

load b) July


• 1036 kWh for months of 30 days

• 1071,36 kWh for months of 31 days

• 967,68 kWh for February in usual year and 1002,24 kWh for February in leap-year.

I reckon that is not necessary to show any graphic of this specific load, because the demand

is constant independently of the season or period. Fig. 4.27 shows an image of the heating

plates installed in another farm that is not Can Barrina, but which has the same technology of

the company LAMAPOR [22].

Fig. 4.27. LAMAPOR heating plates of 100 W. (Source: [22]).

Load 6) Aerobic digester’s motor:

Finally, the last electric load included in this analysis and not put inside the “other loads” group

is the 2-kW motor of the aerobic digester, which gives the energy required by the mix of solid

and dried manure to produce the high-quality fertilizers inside this digester. However, the motor

just works 10 % of the time (again). Thus, the electricity demand can be assumed to be

constant and equal for each hour of the year: Corresponding to the consumption that a 200 W

motor working constantly would have.

This translates to a daily consumption equal to 4,8 kWh and a monthly consumption of:

• 144 kWh for months of 30 days

• 148,8 kWh for months of 31 days

• 134,4 kWh for February in usual year and 139,2 kWh for February in leap-year.

Again, it does not seem necessary to display any chart of this. Let’s see now how the resulting

electrical demand’s curve is developed after analysing all these loads. Thanks to the previous

calculations the hourly distribution of the demand can be known and then the maximum and

Pág. 52 Report

minimum demand scenario can be performed while sizing the EGS proposed in this Thesis.

Total electrical demand:

All the previous analysis was carried out in order to know how the electrical demand works

hourly, and to be able to size the EGS according to the real necessities of Can Barrina.

Obviously, there are many loads that haven’t been considered and even some loads that are

just used in punctual days (i.e. the lawn mowers used in harvesting days) or some loads that

are stopped in some periods (i.e. between reproduction periods of the sows the electric

resistance of the pigs’ farrowing house are closed, normally in in the coldest months). Fig. 4.28

shows the mere summation of the previously analysed loads.

Fig. 4.28. Total electricity consumption by the analysed main loads. (Source: Own).


The chosen circular graphic of Fig. 4.28 is expected to facilitate the comprehension of the

energetic use of the farm; being a circle divided in 8760 parts where each one represents 1 h;

and in each hour it can be appreciated its energetic consumption (measured using the circulars

layers separated 5 kWh from each).

However, it must be taken into account that the real electricity consumption of the farm for

year-and-a-half period is known, so taking these values into account more than the ones

calculated before makes the assessment more realistic. Nonetheless, it must be remembered

that the values obtained were monthly values – remember FGI – making impossible to know

the hourly distribution of the load. Then, it was opted for the following solution:

• The analysis of the main loads is used to calculate the sum of the monthly consumption

of that loads, but the difference with the real monthly demand and this one is distributed

homogenously in each hour of each month. In other words, if the real demand for

February is 6200 kWh but the summation of the main loads for that month is 4695,52

kWh; the remaining 1504,48 kWh are now distributed equally in the 672 hours that

February has (28 days) – meaning 2,2388 kWh summed each hour. This happens for

all the months of the year except the last two.

• The same happens for November and December where the calculated demand is

higher than the real one, since the difference is negative, the total excess energy of

the calculated one (if compared to the real one) is discounted each hour. Then, using

the example of November: The real consumption was 4100 kWh, while the calculated

one is equal to 5017,62 kWh; meaning that the exceeding 917,62 kWh are divided by

the 720 h of November (30 days) and this value is discounted from each hourly

demand. It didn’t happen to have any negative value, so the assumption works

correctly.

For this reason, the mere summation of the analysed loads shown in Fig. 4.28 is not as much

realistic as it is the approximated hourly electricity consumption shown in Fig. 4.29, where the

all the exceeds or lacks of energy have already been included in the total consumption of the

farm. Clearly, if we had known the real hourly electricity consumption of the farm this analysis

would not have been done, but unfortunately, we didn’t know this information. However, there

is a benefit on doing this assessment and is to know which elements are the most demanding

ones and consumes more energy and which ones have less impact in the final consumption:

Information that can be useful for the client of this project.

In Fig. 4.29, the approximated hourly consumption is presented as well as the one of the main

loads, with the idea of comparing the changes. Finally, the days with maximum and minimum

demand are found and presented later on. Hence, the sizing of the EGS is now possible since

the evolution of the electrical demand is known monthly, daily and hourly.

Pág. 54 Report

Fig. 4.29. Comparison between total approximated electricity consumption and electricity

consumption of the main loads. (Source: Own).

The day with maximum demand corresponds to the 1st of August, reaching the peak of

electricity consumption at 17:00 (pm). For that day the total electricity consumption is equal to

743,74 kWh; from which 46 kWh are consumed from 17:00 to 18:00 – being therefore the hour

of maximum consumption during the whole year.

On the other hand, according with this criterion the minimum demand occurs the 1st of

December at 2:00 (am), with an hourly demand equal to 0,2371 kWh and a total daily demand

equal to 126,12 kWh. Nevertheless, due to the approximation of distributing homogeneously

the exceeds and lacks there were obtained at some hours nonsense results: Because the

minimum demand is lower than the electricity consumption of the base-loads, which operates


all the year uninterruptedly. Consequently, the solution taken was to consider the minimum

demand as the lowest electricity consumption of the main loads, which is 1,854 kWh at 4:00

am the 15th of July (however the demand for that day was high, it just happened in that specific

hour: The day with lowest electricity demand still is the 1st of December). This is the minimum

hourly value that must be expected to produce by the EGS independently of the season or

external conditions, but also the day of maximum demand the system must work without

interruptions or faults. In the following section the thermal demand of Can Barrina is studied.

4.3.3. Thermal demand

The electrical demand has already been calculated hourly, but now it is the turn of obtaining

the hourly consumption profile of thermal energy. This makes a lot of sense considering the

premise that in an EGS based on converting a fuel (in this case biogas) into electricity heat

most like be released. Then, even if the biogas obtained in a co-digestion process inside an

anaerobic digester is transformed into electricity in a gas cycle (based on its combustion) or in

a high-temperature fuel cell – such as Solid Oxide Fuel Cell (SOFC) or Molten Carbonate Fuel

Cell (MCFC), with thermal and electrical efficiencies – heat would appear as a result.

Thus, the idea is to study how the farm could take profit of the thermal exceeds of the EGS for

supplying its own thermal demands, if possible. One important point made is the following:

• The thermal loads that are currently using electric systems to produce heat (i.e.

electrical resistance of LAMAPOR of previous section, the ones used for heating the

water…) wouldn’t be studied as thermal loads. Indeed, replacing these systems for

others that can work with biogas would make sense, but the remodelling of the

infrastructure of the farm is out of the scope of this project. The analysis of which loads

could be optimized after installing the EGS is recommended if it is installed in reality,

because there might be a tremendous potential in energy savings.

Going back to the topic, the main thermal load not studied yet is the pig farrowing house, which

must be maintained at 21 ºC all the year (currently done by the already mentioned 72 hot

water-based heating plates; water heated by a diesel boiler). Diesel is used or many purposes

as listed before, so the specific amount used for heating that structure is unknown. Then, the

solution taken was studying the thermal losses in that block. Nowadays, the thermal demand

would be met thanks to the use of the heating plates and the 15 heating pumps of 0,2 HP also

mentioned in section 4.2.2.

Then, the first point to calculate the thermal losses is first to assume that the inside of the pig

farrowing house is always maintained at 21 ºC (actually, it must be at that temperature for the

wellbeing of the recent-born piglets). The dimensions of the walls must also be known; and

they can be obtained from the farm’s design of Annex I, as well as their orientation – important

Pág. 56 Report

to know the radiation gains, as explain later on. It is observed that that block occupies a surface

of 144 m2 (six separated rooms of 6x4 m; with 8 adults sows per room with their babies). The

block is almost facing South (very small deviation), and the roof has a very tiny slope –

neglected in the calculation; it is assumed to be horizontal – and is south oriented as well. The

altitude of the block is equal to 2,5 m. It must be known which are the main walls that conforms

the structure, because otherwise the thermal losses and gains by Sun’s radiation cannot be

calculated, then, these walls are:

1. Wall 1: 24m x 2,5m wall almost South oriented, assumed to face South (γ = 0º). Its

area is equal to 60 m2. All the walls are perpendicular to the ground (β = 90º).

2. Wall 2: 6m x 2,5 m wall East oriented (γ = 90º), with an area of 15 m2.

3. Wall 3: 24m x 2,5m wall North oriented (γ = 180º), with an area of 60 m2.

4. Wall 4: 6m x 2,5 m wall West oriented (γ = 270º), with an area of 15 m2.

5. Roof: 24m x 6m wall enclosing the block, assumed to be horizontal (β = 0º). Its area is

equal to 144 m2.

Once this is known, it must be known the layers that compose the walls – thickness and

thermal conductivity – in order to assess their thermal insulation capacity. The walls and the

roof were installed as insulating surfaces, but they don’t had access to the data referring to

their specific layers and thicknesses. Then, it is assumed to be the industrial wall found in one

exercise of the book Fundamentals of Heat and Mass Transfer [19], for a typical insulating

wall, with the following layers (equal for the roof):

A) Layer 1: 10 cm of concrete, with kc = 1 W·(m·K)-1

B) Layer 2: 2 cm of insulating plaster, with kp = 0,22 W·(m·K)-1

C) Layer 3: 2 cm of fiberglass, with kf = 0,038 W·(m·K)-1

D) Layer 4: 10 cm of concrete, the same as layer 1.

In this case it was repeated the procedure followed in previous section for determining the

thermal resistance (hourly, since the convection coefficient changes accordingly to the outside

temperature and wind speed) of the milk refrigeration tanks. Nonetheless, the formulas are

now adapted for a plane wall, instead of being a cylindric tank. The idea is to use again Eq.

4.7 to know the power losses for each hour, but in this case with the thermal resistance

associated to each wall.

The thermal resistance is composed by the conduction and the convection term. Being a plane

wall, the Reynolds number can be calculated using Eq. 4.9 but with “L” the altitude of the wall

(2,5 m) for all the walls (1, 2, 3 and 4) and the mean value of the longitude and amplitude of

the roof – (24+6)/2 = 15 m. This assumption is done since the Reynolds number is always


calculated for the wind speed perpendicular to the wall, and in this case the wind orientation is

unknown. A similar assumption is also done for all the walls, assuming that the wind blows

identically to all of them (there was not data accessible of the wind direction, and the variation

for convection losses would have been really small, so this effect is neglected). The same air

conditions used for calculating the losses in the milk refrigeration tanks can be used now, since

the temperature in both places can be assumed to be the same (there are separated less than

200 m).

It can be calculated then the Nusselt number once all the Reynolds numbers for the 8760 h of

the year are obtained, but in this case Eq. 4.10 cannot be used since that expression only

worked out for turbulent flows (in this case of air) in a cylinder. Then, Eq. 4.14 is the Nusselt

number for a plane wall having a turbulent flow [19]. Eq. 4.11 can be used to calculate the

convection heat transfer coefficient for each individual wall and the roof.

𝑁𝑢 = 0,0296 · 𝑅𝑒4/5 · 𝑃𝑟1/3 (Eq. 4.14)

Once the convection heat transfer coefficient for the outside (ho) is obtained for every wall and

the roof, the conduction losses that occurs though the layers of the insulating walls can be

obtained as well. In this case, the formulas used also would differ from Eq. 4.8 since the

conduction losses depends also on the geometry of the studied transfer area. Then Eq. 4.15

shows how the total thermal resistance for each wall “w” can be obtained. A term associated

to the inner convection heat transfer coefficient (hi) must also be considered, and it is assumed

to be equal to 30 W/(m2·K). The conduction thermal resistance through layers 1 and 4 is the

same since they are both 10 cm concrete layers, then they can be multiplied per 2. In this case

“L” corresponds to the thickness of each layer of concrete, plaster and fiberglass (Lc, Lp and Lf

respectively).

𝑅𝑡𝑜𝑡𝑤= 𝑅𝑐𝑜𝑛𝑑1𝑤

+ 𝑅𝑐𝑜𝑛𝑑2𝑤+ 𝑅𝑐𝑜𝑛𝑑3𝑤

+ 𝑅𝑐𝑜𝑛𝑑4𝑤+ 𝑅𝑐𝑜𝑛𝑣1𝑤

+ 𝑅𝑐𝑜𝑛𝑣2𝑤=

1

𝐴𝑤·

(𝐿𝑐

𝑘𝑐· 2 +

𝐿𝑝

𝑘𝑝+

𝐿𝑓

𝑘𝑓+

1

ℎ𝑖+

1

ℎ𝑜) (Eq. 4.15)

Having the thermal resistance for all the surfaces, the hourly power losses can be found as it

was done for the refrigeration tanks but in this case for each surface. Multiplying by a time of

1 h for each power loss per wall, and summing the results, it is obtained that 19811,41 kWh

are lost by convection and conduction through the walls of the pig farrowing house (if is always

kept at 21 ºC). The results are obtained considering the ambient temperatures each hour of

the year, and the temperature difference of Eq. 4.8 would be (21-Tamb) in this case.

Nevertheless, for a such big block, the energy provided by the Sun in form of radiation must

be considered, since in many hours the incident radiation heats up the interior of the building.

These calculations are not so easy since the radiation incident to each of the studied walls in

Pág. 58 Report

each individual hour of the year must be then calculated. Here the angles from the Sun’s

position in respect to the Earth (the solar deviation), the latitude, the azimuth, the hour angle

and many others must be considered in order to know the incident radiation to every one of

the five walls (one is the roof) every hour of the year.

Actually, there is a MATLAB code written by the professor of the UPC César García Veloso

that was used in the subject referenced as [23]. This code was originally written to calculate

the incident radiation in a single wall oriented in an angle “γ” from the South – then if is South

oriented γ = 0º – and with and inclination equal to “β” – being β = 0º if the surface is horizontal,

and β = 90º if it is vertical. As an example, Fig. 4.30 a) shows the expected solar irradiation (I)

for the 8th November calculated as the sum of the direct irradiation (Ib) and the diffuse

irradiation (Id) in Barcelona for a vertical wall South oriented. The same graphic is shown in

Fig. 4.30 b) for the 15th July as a comparison.

Fig. 4.30. a) Irradiation (direct and diffuse) the 8th November on a vertical plane wall South oriented at

Barcelona. B) Same graphic for the same wall the 15th July.


First, it is interesting to remark that the reflected irradiation is not included in the graphics of

Fig. 4.30, but it is included in the calculations of the MATLAB code since they are based on

the mean annual values of irradiance at the location of Barcelona. Another interesting detail is

that there are more hours of sun in the second chart, and this happens since summer is the

period with larger day lengths – and the irradiance is higher also. The same calculations where

performed adapting this code but for calculating at the same time a matrix of 5 rows and 8760

columns, where each row is each wall or surface and each column represents the hour of the

year. In this way, the code was adapted for calculating the specific irradiance at each of the

five studied surfaces at each hour of the year.

All the formulas and trigonometric relations used to determine all the solar angles and

parameters hourly would not be commented, since the complexity of that calculations is high

and is considered to be out of the scope of this project, as it would require a deep detail in

solar energy concepts. The specific orientation and slope of each wall – described before –

was then introduced in the code, as well as the specific latitude of the farm (42,002699 º N).

The mean irradiance values of Barcelona were assumed to be the same that those of the farm

location. After filling all the parameters and adapting the code to create the annual hourly matrix

of irradiances in each wall (assuming that at night the radiation is zero, that in reality is not true,

but the effect into the block’s inner temperature can be neglected); all the irradiances per

square meter of each surface each hour of the year were obtained. The next point is assessing

how this irradiance affects the inner temperature.

Consequently, Eq. 4.16 was adopted to calculate the equivalent outside temperature on the

boundary layer between the wall and the air in contact with that wall (Tsol-air), considering the

solar effect at that specific hour. This expression relates the ambient temperature (Tamb), the

exchange of radiation between the surface and the sky (neglected), other parameters such as

the absorptivity of the wall (αs = 0,4 for a typical wall [19]) and the outside convection heat

transfer coefficient (ho; already calculated for each wall and hour to know the convection

thermal resistance) and finally the calculated total irradiance (It).

𝑇𝑠𝑜𝑙−𝑎𝑖𝑟 = 𝑇𝑎𝑚𝑏 − 𝜖𝜎(𝑇𝑠𝑢𝑟𝑓𝑎𝑐𝑒

4−𝑇𝑠𝑘𝑦4)

ℎ𝑜+

𝛼𝑠𝐼𝑡

ℎ𝑜 ≈ 𝑇𝑎𝑚𝑏 +

𝛼𝑠𝐼𝑡

ℎ𝑜 (Eq. 4.16)

The radiation from the wall to the sky is neglected, since those energy losses would be really

small. Once this temperature is known for each of the 5 walls and all the hours of the year: It

can be seen if there would be solar gains by a heat transfer from the outside to the inside if

that “Tsol-air” is higher that the inner temperature each hour, or if in the other hand, that hour

there would be thermal losses. The power gains are calculated as shown in Eq. 4.17, where

“U” is the overall heat transfer coefficient and “Aw” the area of each surface/wall. The product

“U· Aw” can be also expressed as “1/Rtot_w”, using the thermal resistances already calculated

for determining the thermal losses in Eq. 4.15.

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𝑄𝑔𝑎𝑖𝑛𝑠𝑤= 𝑈 · 𝐴𝑤(𝑇𝑠𝑜𝑙−𝑎𝑖𝑟 − 𝑇𝑖𝑛) =

𝑇𝑠𝑜𝑙−𝑎𝑖𝑟−𝑇𝑖𝑛

𝑅𝑡𝑜𝑡𝑤

(Eq. 4.17)

The result is that in many hours there are thermal gains due to the Sun’s radiation that would

derive in less energetic requirements to maintain the interior of the pig farrowing house at 21

ºC. Just to be able to have an idea of the results obtained, Fig. 4.31 shows the thermal gains

per wall during the 23rd January. This day has been chosen because as many others, there

are not gains during the night, and during the day some walls has gains but other does not at

specific hours. A good point to be remarked is that wall 1 (South-faced) is the one the gives

larger solar gains, because the solar irradiance impacts more hours directly than, for instance,

wall 3 (North oriented) which is almost all the time at shadow. Then, in the northern hemisphere

the East-faced wall gives more gains in the morning while the West-faced one gives more

gains in the afternoon.

Fig. 4.31. Energy gains due to solar radiation the 23rd January of standard year. (Source: Own).

From Fig. 4.31 it is really interesting to appreciate that the North-faced wall does not generate

a significant amount of energy gains (a little bit at 12:00 in solar time; the solar noon), and the

roof does not induct energy at all. This can be simply explained by understanding the Sun

position the day of the year that it has been analysed. No matter the day that in solar tracking

systems it is always sought for perpendicular to the solar radiation by the panel surface, since

at perpendicular angles the incident radiation is maximized. Nonetheless, the Sun’s position

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

1,8

2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Egai

ns

(kW

h)

Time (h)

Energy gains (kWh) 23th January

Wall 1 (S) Wall 2 (E) Wall 3 (N) Wall 4 (W) Roof


variates along the year, being the optimal angles in summer around 23º (between the panel

and the solar radiation) and around 61º in winter at Spanish latitude (all Spain is included). In

23rd January the Sun would be at low position, needing higher angles of the surfaces to capture

as much radiation as possible. In this case, there are not tracking systems because the walls

are fixed and they cannot be moved, so the wall facing North would be almost all the day at

shadow and the roof (considered to be horizontal) would be far from the more or less 61º that

optimizes the solar collection: Meaning that an horizontal surface would capture only a small

fraction of all the irradiation entering into the Earth’s atmosphere at that location. This fraction

is not enough for generating solar gains inside the block.

These solar gains have been summed hourly (if any in each specific hour) to the thermal losses

for that hour. In this way the energy balance and the studio of the thermal requirements is more

accurate. The result is an annual demand of 17696,7 kWh to maintain 21 ºC inside the pig

farrowing house. This energy is the useful energy, but here the efficiencies of the diesel boiler

heating up the water and the 15 heating pumps of 0,2 HP should be considered in order to

know the real energy consumption. However, in this section only the useful energy is shown,

further calculations are done in order to assess the energy savings in the economic and

environmental analysis. The useful thermal energy that is desired to be covered by the EGS

every hour of January (as an example) is represented in Fig. 4.32.

Fig. 4.32. Hourly thermal consumption for the standard year in pig farrowing house. (Source: Own).

The coldest days of the month are those with larger thermal demand, as it is logical. A graphic

like this could be shown for all the months of the year, but the results are high demands in

0

1

2

3

4

5

6

7

12

34

56

78

91

11

13

31

55

17

71

99

22

12

43

26

52

87

30

93

31

35

33

75

39

74

19

44

14

63

48

55

07

52

95

51

57

35

95

61

76

39

66

16

83

70

57

27

Eco

ns

(kW

h)

Time (h)

Thermal demand (kWh) for January

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winter and lower demands in summer when, even if in the night usually the temperature at the

farm’s location is lower than 21 ºC, the energy gained during the day usually is enough to

maintain 21 ºC in the inside rooms.

This is the only significative thermal demand associated to the normal activities of the farm.

There could be others, but there are not included in this project since the EGS would be

dimensioned to cover the electrical needs as a priority, and then the possible uses of the

thermal energy derived from the electricity generation would be studied. Hence, this is the main

thermal load considered as it is the largest on most significant one.


5. Biogas production

Once all the thermal demand is known, the next step is to study how the agricultural and cattle

raising residues can be transformed into a useful energy carrier (sizing the technology used to

perform this step). In this project, the usable wastes detailed later on are mainly the slurry – or

liquid part of the manure coming from pigs and cows – and a fraction of the agricultural crops.

Thus, in this section it is studied how these wastes can actually be transformed into

biomethane (or biogas) – which is chosen to be the energy carrier that would be transformed

into useful energy in the last step.

Likewise, the new energetic needs derived from accomplishing this transformation of energy

are also assessed, since this energy can be an extra input which could suppose a problem in

terms of monetary expenses or, on the other hand, can be fully covered by the final energy

produced by the EGS itself. Since the device in charge of fulfilling the conversion from organic

wastes to biomethane is an anaerobic biodigester; there is a variable thermal demand – totally

dependent on ambient conditions – which must be calculated in order to study the feasibility

of an essential part of the proposed EGS.

5.1. Transformation of residues into biogas

5.1.1. Usable wastes and resources produced in the farm’s normal activity

In this section numbers regarding the real production of wastes of Can Barrina are presented

and analysed, with the main idea of understanding the potential of the activity based on

producing biomethane. Obviously, constraint of all this Master Thesis is to limit the resources

used by the EGS to the ones derived from the farm’s activity itself: And not oversizing the

system by, in example, accepting other farms’ residues.

Let’s focus then on the amount of manure produced in the farm each year. Indeed, the result

of raising 251 adult cows, 350 adult sows, 60 calves and a big number of piglets leads to a

scenario where a lot of manure is produced – as a result of the individual digestion process of

each animal. Since all the manure is recollected and then placed in the same facilities, Eduard

knows approximately how much of this waste is produced. Table shows the available

wastes/resources that are yearly produced – from which it seems important to highlight that:

• The residual water is the one coming from cleaning the slurry’s canalization and pipes,

the pig house’s floor and the cowshed. All this water is led to the slurry pools 1, 2 and

3 presented in the point 4.1.2 of this project. They are included in the available

resources to produce the biomethane since this water is mixed with the slurry in the

pools, being a small fraction of what fills them.

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• The agricultural crops harvested in autumn are very variable depending on the year,

so the highest and smallest values recorded in the last 20 years are presented in Table.

The mean or expected value for this harvest goes around 1650 tonnes per year [t/year].

• The agricultural crops harvested in summer are really constant regardless of the year,

fixed around 1500 t/year.

• The solid manure or muck is calculated considering that each cow produces 50 kg/day

while a calve produces 15 kg/day (according to [24]), each adult sow produces 3,6

kg/day and a pregnant one 6,4 kg/day (according to [25]). This would translate into

5635,6 kg/year coming from the animals living in Can Barrina. This assumption was

done since we just had access to the amount of fertilizers produced with this muck.

Resource/waste Quantity Units It will be used?

Liquid manure (slurry) 3390,44 m3/year Yes, all of it

Solid manure (muck) 5635,6 t/year No: Needed for making fertilizers

Residual water 182,5 m3/year Yes, all of it

Spring harvest 1500 t/year No, for reasons explained later

Autumn harvest 850-3000 t/year Yes, a fraction

Table 5.1. Yearly generated wastes/resources for producing the biomethane. (Source:Own).

5.1.2. Influence of ripening, silage and composition of the crops

Another important matter is commented in this section and it is when the maize, wheat and

wins would be harvested; in order to have the best possible methane production yield. In fact,

there are many scientific articles posted in Science Direct highlighting when is the best moment

to harvest the crops. In example, the article called Biogas production from maize and dairy

cattle manure – Influence of biomass composition on the methane yield sustains that “the

optimum harvesting time for maize is reached at dry mater content of 30-35%” [26]. Actually,

this article describes a really similar process to the one expected to perform in this project,

since it works with the same cereals and with cows’ manure (without including the pigs’ one

as a difference).

When studying the potential of a biomass resource for producing methane by an anaerobic

digestion, there is a quality parameter that allows the assessment of each type of cereal or


plant, and it is Volatile Solid (VS) matter contend. Actually, the biogas production is usually

referred or given in norm litre (NI) of biogas per kg of VS associated to each specific product

that will compose the mix transformed into biomethane [26]–[33]. In the next section this value

for the existing wastes/resources in Can Barrina is found and after used for developing the

calculations of the biogas production. However, now what concern us most is when and under

what conditions the cereals and plants cultivated should be harvested for biomethane optimal

production yield.

Besides, silaging of the maize, wheat or wins would increase the methane yield by at least

25 % if compared to green and non-conserved crops [26] [27]. This fact was observed

comparing a maize – of variety Ribera (FAO308) – recollected the same day but half of it was

ensiled (after being chopped, compacted and stored under anoxic conditions) and the

remaining equivalent part was left green and non-conserved. After some weeks, the maize put

in silage had 289 Nl CH4 VS-1 (±10,8 Nl CH4 VS-1) while the green one had 225 Nl CH4 VS-1

(±7,1 Nl CH4 VS-1) [26]. This happens since inside the silage the degradation of sugars is

smaller generating less energy losses. What’s more, a correct silage process requires at least

dry matter (DM) contents of the plants higher than 28 % to “avoid substantial silage effluent

losses” and not higher than 35 % to “avoid difficulties in silage stock compaction and risk of

silage reheating and mold development”; according to [33].

Coming back to the ripening state of the cereals it is interesting to say that at higher DM

contents better it would be the biomass yield, leading to higher biomethane production rates.

For this reason, the ripening state is divided in three main groups depending on its nutrient

composition, DM content, gross energy and organic DM content [26] [34]:

1. Milk ripeness: Moisture content in grain around 55-60 %.

2. Wax ripeness: Moisture content in grain around 45-48 %.

3. Full ripeness: Moisture content in grain around 23-28 %.

o Note: There are more groups: being all of them; grain growth, kernel milk, line,

milk-wax, wax and full ripeness [34].

Clearly, at higher moisture rates the DM content would be lower, and so would be the amount

of CH4 that can be extracted from the same crops. Fig. 5.1 shows the biomass yield achieved

from different ripening varieties of maize at different stages of vegetation (changes in DM).

Besides, the methane yield per hectare of land cultivated for the previously analysed ripening

groups and its state of vegetation is presented in form of graphic in Fig. 5.2; where “Tonale”,

“PR34G14” and “LZM 600” are different varieties of late ripening maize.

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Fig. 5.1. Biomass yield of late ripening maize varieties at different stages of vegetation. (Source: [26])

Fig. 5.2. Methane yield per hectare of late ripening maize varieties at different stages of vegetation

with standard deviation from three replicates per variety and vegetation stage. (Source: [26])

As it can be clearly appreciated in the previous figures, the methane yield – and so the VS

from biomass – increases when the ripeness of the late ripening maize is higher. Besides, the

moisture content is even smaller. In other words, a cereal is optimally harvested for biogas

production purposes “when the product from specific methane yield and VS yield per hectare

reaches a maximum” [26]. Nevertheless, the methane yield per hectare is predominantly

dependant on the maize variety and the already mentioned time of harvesting which influences

its ripeness. Previously it was showed that for late ripening maize the optimal harvesting time

it’s at full ripeness.

Nonetheless, the type of maize cultivated in Can Barrina is not late ripening type as there are


two cultivation periods of six months, and the land needs some time to recover its fertility. Then,

in standard types of maize the optimal harvesting time “occurs at the end of wax ripeness when

the DM content takes a value around 35-39 %” [26]. It is also commented in this article that on

fertile locations late ripening varieties of the different cereals are preferred for biogas

production applications, but this is a recommendation not supported in this project since it

would alter the composition of the cows’ feed and also the harvesting periods already

optimized by the farmers since more than 80 years ago.

Finally, it is remarked that the parts of the cereal or plant itself that enters inside the anaerobic

digester would definitely make a difference in the final biomethane production. Certainly, for

the case of maize using all the cereal including the stem and leaves of the plant would translate

in a greater yield than just using the crops and corns. Fig. 5.3 makes a comparison in how

much affect the final yield using different parts of standard maize.

Fig. 5.3. Biomass yield from maize corns, corn and cob mix, the plant without the corn and the cobs

(CCM) and the whole plant at different ripeness stages. (Source: [26]).

In reality, the results shown in Fig. 5.3 adapts perfectly to the harvesting technology already

used in Can Barrina; because the machine already takes all the cereal plants chopping the

whole plant with the intention of putting the resultant product in a silage (where it ferments,

remains stored and is extracted when it is required). The solution would be then to leave apart

some of the cultivated cereals for ensuring the supply of the essential amount needed to run

the biodigester at optimal conditions.

Finally, the last thing that should be looked at is the performance offered by different types of

plants species to produce biogas and which portion of wheat and wins should be included (if

any). The vast majority of the articles already listed ([26]–[33]) noticed that maize is a great

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option to consider due to its high DM and VS content per unit mass and volume; making its

Biochemical Methane Potential (BMP) higher than other plants. Nevertheless, it’s not the only

option and in the article Assessment of energy crops alternative to maize for biogas production

in the Greater Region [27], many other plants are compared to the maize’s performance. Table

5.2 shows the most convenient crops to compete against maize for these purposes.

Table 5.2. “Plant material, cropping details, number of samples analysed, total solid (TS) and VS

contents”. (Source: [27]).

As it can be seen in Table 5.2, maize harvested at late winter offers the best conditions

(maximizing the VS and TS fraction), but in return it augments the cultivation period in 3

months, what’s not compatible with Can Barrina’s interests. In short cultivation periods hemp

and miscanthus are the only crops that can compete against the maize (in cultivation periods

from spring to late autumn), being the last one the only recommended alternative by [27]. Just

for interest, Fig. 5.4 shows the comparison of the CH4 production kinetics for maize versus

miscanthus. The fact that maize’s reaction is faster – occurring mostly in the first 20 days –

while the miscanthus’ reaction is slower – occurring in the first 40 days – is highlighted since

for long periods this last plant’s CH4 production can be actually better than for maize.

Fig. 5.4. Comparison of CH4 production kinetics between maize and miscanthus silages during 42

days and its prospects. (Source: [27]).


To end with this discussion, Fig. 5.5 shows the comparison of many different crop species to

illustrate how the BMPs and the biomethane yields are affected depending on the cultivated

plant (see Annex III). It can be appreciated that in this case the biomethane yield of maize is

larger by far than the one for miscanthus, even if in the experiment showed in Fig. 5.4 the CH4

total production can be higher for this last plant. This happens since the vast majority of the

methane production in maize’s digestion occurs in the first 20 days, while for miscanthus it

makes more time. The result is that for obtaining the same amount of biogas it would be

needed more time (and constant energy supply) for miscanthus than for maize.

Fig. 5.5. a) Influence of crop species on biomass yield, BMP and biomethane in different species. b)

Influence of the harvest years (2009, 2010 and 2011) on the biomass yield, BMP and biomethane yield

for maize, miscanthus and sorghum. (Source: [27]).

To sum up, it seems clear that maize is the best option for biomethane production purposes,

presenting the best yields per mass, volume and cultivated hectare. This led to the conclusion

that wheat and wins (the other main crops cultivated in the farm) are not a good enough

alternative to be mixed with maize, since the conversion efficiency might be then considerably

lowered down. Hence, a part of the cultivated maize will be left apart to be siled (as it is currently

done), but in this case for energy production reasons and not just as cow feed.

Regarding the spring and autumn harvests, it would be used a fixed part of them which is the

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optimal one for biogas production purposes; calculated in section 5.1.4. However, the

variability of the autumn harvest would generate some years of monetary losses contemplated

in the economic analysis – usually there are exceeds in production if compared with the

2249,13 t/year that the cows consume, and pigs eat a special feed not derived from these

crops. That is to say, is the turn for calculating the amount of biogas that can be produced in

the anaerobic biodigester by taking profit of the wastes/resources showed in Table 5.1.

5.1.3. Influence of the characteristics of manure

When producing biogas with animal manure, it is commonly mixed with biomass with a high

percentage of VS to maximize the methane release. In the previous section it was analysed

how the characteristics, treatments and composition of the biomass can alter the biogas

production, and in this section the manure is assessed. The only problem found on this part of

the project was that we didn’t have access to the detailed composition of the manure of Can

Barrina, so in the calculations of next section the type of liquid manure is assumed to be the

same than the one used in the experiment carried out in the article of J. Ning named

Simultaneous biogas and biogas slurry production from co-digestion of pig manure and corn

straw: Performance optimization and microbial community shift [35]. The associated properties

needed for the calculations are then presented in next section.

Some of the typical compositions of cows’ and pigs’ manures are listed, for seeing how the

alimentation of the livestock affects the quality of the manure in terms of CH4 production

potential. Starting with cows, it was first found that there is a direct relation between their diets

and daily milk production with their methane yield. Table 5.3 shows different diets for cows

changing the proportion of concentrate, hay, grass silage and maize silage in their feed, and

Table 5.4 shows how each diet affects to the composition of the dairy manure and to the gas

yield parameters. Dairy-1 and 2 have low milk yield, dairy-3 and 4 medium milk yield, and the

last two high milk yield. The result is that the manures with the higher “crude protein levels

(dairy-1, 3 and 6) gave higher methane yields during anaerobic digestion”, being dairy-3 the

one that offers higher specific methane yield of 166,3 Nl CH4 (kg VS) -1 ;according to [26].

Table 5.3. Dairy cow diet composition and milk yield results. (Source: [26]).


Table 5.4. Compoition of dairy cow manure and biogas/methane yields. (Source: [26]).

Nevertheless, the milk yield of the cows in Can Barrina is around 26 L/day as mentioned in

section 4.3.2. Besides, the diet of those cows is the following per 52 kg of cow feed (two

servings; remember that each cow eats 26 kg of the feed mix every day):

• 47,4 kg came from local cultivations

o 21,5 kg of siled maize

o 8 kg of wheat silage

o 8 kg of wins and bagasse silage

o 1 kg of grass

o 4,5 kg of a mixture of barley, maize, orange and minerals (not siled)

• 4,6 kg are purchased

o 3 kg of soybeans

o 1,6 kg of maize flavour

The result is that probably dairy-6 is the most similar one to the actual cows’ diet (measuring

the milk production yields and expected DM concentrates of the previously described diet).

However, either if these values are required for the calculations or not for the biomethane

production calculations, they won’t be used since they’re related to solid manure and not liquid,

as it would be used in this project – the solution is presented in next section.

On the other hand, the pigs’ manure also would affect to the methane yield depending on some

parameters. The affectations of the diet to the biogas yield are going to have an important role

as well as it happened for the cows. Nevertheless, I believe it’s not necessary to show

comparison between different diets of the pigs again since the idea of why a diet richer in maize

silage and kilograms of DM lead to a manure also richer in DM; and higher methane yields for

the reasons already exposed when the crops properties’ influence were commented in the

previous section. Nonetheless, it was found the exact composition for pig slurry mixed with

maize (corns), which can be seen in next section in Table 5.5.

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5.1.4. Anaerobic digestion and biogas production

Biochemically speaking, the calculation of the biogas production by making the chemical

balances and taking into account the decomposition of the various materials inside the

biodigester is really complicated, and it could be studied as a Master Thesis itself if entering in

detail on how those reactions can be improved to upsurge the anaerobic reaction yield. For

example, in the article named A new algorithm to characterize biodegradability of biomass

during anaerobic digestion: Influence of lignin concentration on methane production potential

([29]), some of the internal chemical reactions that occurs inside the biodigester are studied to

know how the effect of lignin in the biomass would affect the final biogas production rates.

Nevertheless, I reckon that entering at this point of detail is out of the scope of an engineering

process; it is only recommended the reading of this article if it is for personal interest. The

calculations that are now presented would use carbon/nitrogen relations (C/N) that exist for

the experiment using pigs’ liquid manure mixed with maize (similar to the wastes/resources

that would be used in his project) extracted from the article [35]. For finding these C/N, the

chemical balances and calculations had already been done before the results were calculated,

and the results derived from these relations would be used for the calculations of this project.

The substrates used in the commented experiment are showed in Table 5.5.

Table 5.5. Characteristics of the reactants used for the co-digestion of pig slurry and corn straw of

article [35]. (Source: [35]).

It can be interesting to explain why inoculum is included in Table 5.5 for the experiment of that

article, as well as in many other articles regarding biomethane production. Actually, inoculum

appears as a result of an internal circulation in the anaerobic reactor when food starch is “used

as feedstock under mesophilic condition (37 ± 1 ºC)” [35]. Thereupon, this new substance is

also evaluated in the calculations of the C/N for this and similar experiments which included

the fermentation of crops and manure.


It should be remarked that this fermentation happens thanks to the action of

microorganisms/bacteria start a process of microbial decomposition of the residues and crops.

Starting with an aerobic phase, the organic matter is slowly and progressively subjected to

anaerobic conditions (until there is no oxygen), substituting O2 by other inorganic oxidised

gases in its respiratory metabolism; such as nitrite and sulphite, which under an oxidation-

reduction conditions are reduced to nitrogen and sulphur hydrogen gases (from -50 mV to -

100 mV). The reduction potential would increasingly go up and when -150 mV to -300 mV are

reached, the CH4 production begins. [36]

Just to visualize how the three continuous stirred tanks reactors were placed and connected

between them in the experiment carried out in the article [35], Fig. 5.6 shows the experimental

devices that involved the anaerobic digestion. In that experiment, each of the identical reactors

were used to compare how the influence of changing the TS and the organic loading rate (in

other words, the input rate of organic matter into the digestor) are affecting the biogas yield;

giving the results of the optimal C/N relation for the proposed wastes/resources to be used.

Actually, comparing the influence of the C/N ratio in the digester biogas yield, the best CH4

proportion appeared for C/N ratio of 30 (being a proportion of 66,08 %: for 20 it would be

63,28 %, for 25 around 62,17 % and for 35 only 58,35 %) – In the case of 35 C/N ratio it

happened that the “methanogenic microorganisms are more sensitive to pH than acidogenesis

microorganisms”. [35]

Fig. 5.6. Experimental devices and interconnections between them for [35]. (Source: [35]).

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Despite this, the mentioned article defends and demonstrated again the conclusions already

found out in similar articles like the one of the Doctor Kiros Hagos [37]; which argued that the

best C/N ratio for this wates/resources is equal to 25 and not 30, since it has the higher biogas

production rate (SBP). It doesn’t mean that the proportion of methane in all the gas generated

is higher, but the reaction’s speed is. Therefore, it can be generated more CH4 in less time at

a C/N ratio of 25 than at 30, becoming the new optimal one. In Fig. 5.7 it can be appreciated

the evolution of the SBP and the methane proportion depending on the C/N ratio.

Fig. 5.7. a) SBR results depending on C/N ratio, b) CH4 production depending on C/N ratio; both

obtained from the results of the three studied reactors in (Source: [35]).

As it can be deduced in Fig. 5.7 a), the highest SBP was found the day 83 of the experiment

for a C/N ratio of 25. Nevertheless, for this project the C/N ratio of 30 was chosen instead of

25 as the best option for the requirements of our client for the following reasons:

1. A C/N ratio of 30 offers higher proportion of CH4 per each volume unit of total biogas

produced. If the proportion is equal to 66,08 % as mentioned before, this means that

the remaining 33,92 % of the biogas is composed by unwanted products of the co-

digestion of animal manure and maize, such as CO2, N2, CO, H2S or O2.

o As one of the proposed alternatives to transform this biomethane into electricity

is to reform the biogas to obtain pure CH4, more energy would be needed to

obtain the same amount of methane in the refining tank if C/N ratio had been

25. Clearly, there would be more CH4 at our disposal because a bit more biogas

would be generated (in mass and volume terms). However, this biogas would

be of lower quality so less CH4 would be extracted per unit mass/volume

entered into the refining tank.

o The other alternative – the Fuel Cell (Solid Oxide type) – also presents


disadvantages if using biogas of lower quality (intended as biogas with higher

impurities such as CO2, N2 and SO2). This is due to the fact that specially CO2

reduces its useful life cycle, so having biogas with the higher proportion as

possible helps protracting the time that the Fuel Cell can work.

2. The amounts of biogas have been calculated for both options, and both results were

largely sufficient to cover Can Barrina’s demand. In this way, it makes sense to opt for

quality instead of quantity: Specially while the biogas production time does not suppose

a problem and enables meeting the demand at any time.

An interesting detail to consider is that this C/N ratio can be regulated by putting more or less

amount of maize per mass unit (not volume, crucial importance for the calculations) of manure

– since pig manure has a C/N ratio equal to 13,45:1 while corn straw 294,38:1 (maize can be

put under silage to enhance the biogas yield), values obtained from Table 5.5. In other words,

now it is possible to calculate the amount of maize that should be extracted from the total

harvested crops to ensure the desired C/N ratio of 30:1; taking into account that the liquid

manure used would be the 3390,44 m3/year generated in the farm plus the 182,5 m3/year of

residual water. Thus, 3572,94 m3/year of manure are considered as the available resource.

For the reasons explained in section 5.1.1, residual water is mixed with the liquid manure and

it would be assumed that it does not suppose a change in its composition since it’s only a

5,38 % (actually, this water drags also some manure when the canalizations are cleaned).

Besides, the density of manure can be assumed to be the same as the water density, 1000

kg/m3 [23]. Hence, it is expected to find out how many tonnes of maize are necessary to ensure

that the 3572,94 t/year of manure mixed with that maize have a C/N relation of 30:1. These

calculations are now shown, being a simple mass balance using the specific C/N ratios of

manure and maize:

𝐶𝑁𝑡𝑜𝑡𝑎𝑙 = 𝐶𝑁𝑚𝑎𝑛𝑢𝑟𝑒 · [𝑚𝑎𝑛𝑢𝑟𝑒] + 𝐶𝑁𝑚𝑎𝑖𝑧𝑒 · [𝑚𝑎𝑖𝑧𝑒] = 𝐶𝑁𝑚𝑎𝑛𝑢𝑟𝑒 ·𝑚𝑚𝑎𝑛𝑢𝑟𝑒

𝑚𝑡𝑜𝑡𝑎𝑙+ 𝐶𝑁𝑚𝑎𝑖𝑧𝑒 ·

𝑚𝑚𝑎𝑖𝑧𝑒

𝑚𝑡𝑜𝑡𝑎𝑙→ 30 = 13,45 ·

3572,94

3572,94+𝑥+ 294,38 ·

𝑥

3572,94+𝑥→ 𝑆𝑂𝐿𝑉𝐸(𝑥) → 𝑥 = 223,602 𝑡/𝑦𝑒𝑎𝑟

This means that for one year 223,602 t/year of maize should be now deviated for biogas

production purposes and then put in silage to provide higher methane yields for the same

amount of maize. If this maize is not treated, it’s C/N ratio would be no longer 294,38:1,

becoming instead 227,8:1 (from Table 5.5). Repeating the previous mass balance, the needed

amount of maize would be then equal to 298,95 t/year, supposing an increment of a 31,23 %

on the required maize. Here it should be considered what is more important for the farm’s

owners: Minimize the amount of maize used in biogas production activities or, in contrary,

avoid putting some maize in a silage boosting its C/N ratio.

According to the farm’s owner, it is more interesting to minimize the amount of maize required

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in the biodigester, so 223,602 tonnes of maize might be harvested every year in their optimal

ripeness stage for being siled and then added to the biodigester. However, the assumption of

neglecting the effect of inoculum in the total amount of maize could be made. It was opted for

calculating how the effect of including 36 t/year of treated inoculum would affect to this amount

of biomass needed to ensure the desired C/N ratio, and the mass balance would be then:

𝐶𝑁𝑡𝑜𝑡𝑎𝑙 = 𝐶𝑁𝑚𝑎𝑛𝑢𝑟𝑒 · [𝑚𝑎𝑛𝑢𝑟𝑒] + 𝐶𝑁𝑚𝑎𝑖𝑧𝑒 · [𝑚𝑎𝑖𝑧𝑒] + 𝐶𝑁𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚 · [𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚] =

= 𝐶𝑁𝑚𝑎𝑛𝑢𝑟𝑒 ·𝑚𝑚𝑎𝑛𝑢𝑟𝑒

𝑚𝑡𝑜𝑡𝑎𝑙+ 𝐶𝑁𝑚𝑎𝑖𝑧𝑒 ·

𝑚𝑚𝑎𝑖𝑧𝑒

𝑚𝑡𝑜𝑡𝑎𝑙+ 𝐶𝑁𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚 ·

𝑚𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚

𝑚𝑡𝑜𝑡𝑎𝑙→ 30 = 13,45 ·

3572,94

3572,94+𝑥+36+ 294,38 ·

𝑥

3572,94+𝑥+36+ 9,18 ·

36

3572,94+𝑥+36→ 𝑆𝑂𝐿𝑉𝐸(𝑥) → 𝑥 = 226,5 𝑡/𝑦𝑒𝑎𝑟

The deviation on the total maize needed if inoculum is considered to take action in the co-

digestion process is lower than 3 t/year, but actually, it is taken into account to make the

analysis more realistic. Then, 226,5 t/year of maize are going to be harvested just for biogas

production purposes, and the impact of substituting this amount of maize from the cow feed is

assessed in the economic analysis. It would suppose a 15,1 % of the autumn’s harvest. Table

5.6 shows then the used wates/resources.

Resource/waste Mass (T/year)

Manure + residual water 3572,94

Maize 226,5

Inoculum 36

Table 5.6. Amount of each of the elements involved in the anaerobic co-digestion. (Source: Own).

Then, let’s now focus on explaining how the amount of methane that can be produced by using

the wastes/resources in the quantities already mentioned. An important assumption is done:

• The methane production is constant all over the year, since the entrance of treated

maize and manure can be easily regulated to have a constant production all over the

year (maize is conserved in a silage and slurry can be stored in pools 1 and 2 to

regulate the fluxes).

To obtain the biogas production it is important to know first the percentage of TS in the mix of

biomass, manure and inoculum, and then which fraction of that percentage corresponds to

VS. Eq. 5.1 shows how the TS of the mix (TSmix) are calculated, and Eq. 5.2 shows similarly


the equations to find out the percentage of VS (VSmix).

𝑇𝑆𝑚𝑖𝑥 =𝑚𝑚𝑎𝑛𝑢𝑟𝑒·𝑇𝑆𝑚𝑎𝑛𝑢𝑟𝑒+𝑚𝑚𝑎𝑖𝑧𝑒·𝑇𝑆𝑚𝑎𝑖𝑧𝑒+𝑚𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚·𝑇𝑆𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚

𝑚𝑚𝑎𝑛𝑢𝑟𝑒+𝑚𝑚𝑎𝑖𝑧𝑒+𝑚𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚 (Eq. 5.1)

𝑉𝑆𝑚𝑖𝑥 =𝑚𝑚𝑎𝑛·𝑇𝑆𝑚𝑎𝑛·𝑉𝑆𝑚𝑎𝑛+𝑚𝑚𝑎𝑖·𝑇𝑆𝑚𝑎𝑖·𝑉𝑆𝑚𝑎𝑖+𝑚𝑖𝑛𝑜𝑐·𝑇𝑆𝑖𝑛𝑜𝑐·𝑉𝑆𝑖𝑛𝑜𝑐

𝑚𝑚𝑎𝑛+𝑚𝑚𝑎𝑖+𝑚𝑖𝑛𝑜𝑐 (Eq. 5.2)

As a matter of a fact, the VS are the ones responsible of producing the CH4 after the bacteria

and microorganisms decompose the biomass and wastes. For the raw material used in this

project it has been found a relation between the VS remaining at the end of the decomposition

of maize and manure and the methane that is released while they are decomposed: And it is

equal to 0,5 m3CH4/kgVS (remaining) [23]. Moreover, it can be also approximated that haf of

the VS are not decomposed in form of CH4; being 0,5 kgVSrem/kgVSmix. After summing them

proportionally to the relative mass flow maize and manure (and assuming that the affectation

of the inoculum can be neglected) it can be found that the remaining mix has a total TS

percentage of 5 % (following the estimations done at [35]).VS remaining percentage (VSrem) is

calculated as shown in Eq. 5.3; resulting in a 4,09 %. Finally, the balance of Eq. 5.4 is used to

estimate the total CH4 production.

𝑉𝑆𝑟𝑒𝑚 =𝑇𝑆𝑟𝑒𝑚

𝑇𝑆𝑚𝑖𝑥· 𝑉𝑆𝑚𝑖𝑥 (Eq. 5.3)

𝑚𝑚𝑖𝑥 [𝑘𝑔 𝑚𝑖𝑥/𝑦𝑒𝑎𝑟 ] ·𝑉𝑆𝑟𝑒𝑚 [𝑘𝑔 𝑉𝑆]

1 [𝑘𝑔 𝑚𝑖𝑥]·

0,5 [𝑘𝑔 𝑉𝑆 𝑟𝑒𝑚]

1 [𝑘𝑔 𝑉𝑆]·

0,5 [𝑁𝑚3𝐶𝐻4]

1 [𝑘𝑔 𝑉𝑆 𝑟𝑒𝑚] (Eq. 5.4)

From Eq. 5.1 it is found that the TS percentage from the mix is 34,01 %, then the VS of that

mix is calculated in Eq. 5.2 being equal to 27,83 %. From Eq. 5.3. the remaining CS percentage

is found, and considering a TS of 5 % the result is a 4,09 %, that applying the balance of Eq.5.4

leads to a CH4 production of 55913,5 Nm3 CH4/year. Taking the assumption made previously

of constant production, it can be concluded that the methane production would be equal to

153,187 Nm3/day, or 6,38 Nm3/h. In mass terms, assuming a density for the CH4 equal to 0,657

kg/m3 ([23]), the yearly generated mass ascends to 36,73 t/year.

The high heating value (HHV) of methane is equal to 39,8 MJ/m3 (in mass terms 15,4 kWh/kg)

and the low heating value (LHV) is equal to 35,8 MJ/m3 (13,9 kWh/kg) [38]. Therefore, it can

be easily calculated the available power produced each day using the LHV, being 1523,366

kWh per day. Assuming a standard efficiency of the burning process of 90 %, it can be

expected to have 1371,03 kWh per day at the farm’s disposal in form of CH4 existing inside

the mix of gases that compose the generated biogas.

Nonetheless, this methane is would suppose approximately a 66,08 % of the biogas and the

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remaining 33,92 % would mainly be CO2, N2, O2 and CO (in volume terms). The expected

composition approximated of the biogas generated would be the one shown at Table 5.7 –

using the approximations made at [39]. How the CH4 is extracted or used in the different

technologies is deeply discussed in section 6.

Constituents % composition

Methane, CH4 66,08

Carbon dioxide, CO2 30,6

Nitrogen, N2 0,5

Hydrogen, H2 0,5

Carbon monoxide, CO 1

Oxygen, O2 0,92

Hydrogen sulfide, H2S 0,4

Table 5.7. Approximated composition of the raw biogas from typical proportions. (Source: [39]).

It is necessary to know also the total biogas volume and density for further calculations –

remember that the 55918,5 m3 of CH4 are only the results for the methane production, there

are other products. Table 5.8 shows the percentage, total volume of each product that forms

the biogas, their density (from [40]; at standard 25 ºC and 1 atm) and finally the total mass of

each gas (calculated as mass = volume · density). The total results of volume and mass are

shown, as well as the biogas density obtained by dividing the total mass per the total volume

of biogas.

Constituents % composition Volume (m3) Density (kg/m3) Mass (kg)

Methane, CH4 66,08 55918,50 0,657 36738,45

Carbon dioxide, CO2 30,6 25894,46 1,842 47697,60

Nitrogen, N2 0,5 423,11 1,165 492,93

Hydrogen, H2 0,5 423,11 0,0893 37,78

Carbon monoxide, CO 1 846,22 1,165 985,85

Oxygen, O2 0,92 778,53 1,331 1036,22

Hydrogen sulfide, H2S 0,4 338,49 1,434 485,39

TOTAL 100 84622,43 1,0337 87474,23

Table 5.8. Percentage, volume, density and mass of each product per year and total biogas

production (mass, volume and mean density). (Source: Own).


Then, it is known that the biogas production would be equal to 84622,43 m3/year, or in mass

terms, 87474,23 kg/year – from which the biomethane fraction would be used to obtain energy.

5.1.5. Production of coproducts

Indeed, in an anaerobic digestion not only biogas is generated. As we saw previously only the

VS content in the manure and biomass mix would release the CH4 after the microbiological

activity, but the remaining solids that are not volatile would slowly be sedimented at the bottom

of the tank. Moreover, there is still a liquid fraction of the mix that won’t produce neither biogas

nor solid fertilizers; and would appear in form of liquid coproducts. Then the coproducts are

divided in [41]:

• Solid coproducts: Fibre-based products, fertilizers, compost, amendments and

bedding.

• Liquid coproducts: Flush water, and concentrated fertilizers.

Actually, the coproducts of an anaerobic digestion are quite valuable in the fertilizers market.

The solid coproducts are always taken out from the digester constantly to be able to add new

biomass and manure mix into the tank, and they are medium-quality fertilizers [41]. They can

be assumed to lower quality than the ones already produced in the farm in the aerobic

digesters presented in previous sections.

Besides, the liquid coproducts would be of higher quality than the manure itself (without

passing through the co-digestion process). This happens since the bio-fertilizer produced in

that process has a high content of NH4, beneficious for the properties desired in a fertilizer [42].

Germany is the worldwide leader in terms of optimizing the co-digestion processes and giving

a usage to all the coproducts. Fig. 5.8 shows the typical cycle of that process, and where the

biogas and those coproducts are typically used.

The storing tanks for the liquid and solid coproducts must be sized taking into account the

duration of the periods between one selling and the next one. In other words, the size of both

tanks depends on the frequency at which the fertilizers are sold to external buyers, and this

depends on the farm’s policy. In the case of liquid fertilizers there must be a pump that allows

charging trucks to transport them. On the other hand, the tank for solid fertilizers could be

similar to the one already being used in Can Barrina, but prefereably the products won’t be

mixed since their qualities (and then selling prices) may change.

To calculate the annual production of the different coproducts the equation of mass

conservation is applied (see Eq. 5.5). It is already known the biomass and manure mix input

(3835,440 t/year), as well as the biogas produced each year (87474,23 kg/year). Then 3747,97

t/year of coproducts would be extracted from the biodigester. Now, it is only desired to know

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which fraction is liquid and which is solid, and this is done by calculating which part of the TS

of the mix has not been transformed into biogas.

Fig. 5.8. Biogas production cycle. (Source: [41]).

∑ 𝑚𝑖𝑛 = ∑ 𝑚𝑜𝑢𝑡 → 𝑚𝑚𝑖𝑥 = 𝑚𝑏𝑖𝑜𝑔𝑎𝑠 + 𝑚𝑐𝑜𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 (Eq. 5.5)

So, the TS fraction of the mix during the co-digestion was said to be a 5 % of the mix, from

which 4,09 % is VS (remember Eq. 5.3). The same proportion is assumed in the coproducts,

so only 5 % is going to be transformed into solid fertilizers, and the remaining 95 % would stay

liquid (the vast majority of the mix is made of slurry, in digesters where the solid part is used

the results would change). Then, the coproducts production is approximated to be:

• Liquid coproduct: 3560,57 t/year

• Solid coproduct: 187,4 t/year


The methods for extracting those co-products are going to be detailed in next sections, but

with total security, it would be needed a pump for the liquid part and a mechanical system for

the solid one.

5.1.6. Sizing and operation of the biodigester

To size the anaerobic biodigester it is essential to estimate the duration of co-digestion periods.

The biogas generated would be necessarily driven to an external tank where it could be stored,

and by this way it can be introduced more manure and biomass to keep running the process.

In larger tanks with more capacity, more methane can be produced in a single biogas

production cycle, but this depends on the disposed amount of biomass and manure. The idea

is that it can be put new feed to the digester:

• Every day or hour in a constant flux (like it is done in [35]). In this option the biogas is

extracted continuously from the digester and new manure and biomass is added

every day/hour.

• In larger cycles leaving a gap time between one day of refilling the digester and

another one (like it is done in [26], where there are cycles of 36 days for studying the

biomethane yield). The idea is that all the mix and biogas is extracted before putting

new mix in the digester, starting the cycle again.

In both options the co-digestion must be run at a constant temperature of 37 ± 1 ºC, but with

the difference that in the 1st process biogas is produced in an almost identical flux and in the

2nd one biogas is produced in cycles of some days (each cycle can be considered as identical).

Actually, it has been decided to put a constant flux every hour for the following reasons:

a. Introducing the biomass and manure mix each hour allows to regulate constantly the

state of the co-digestion as well as controlling the evolution of the microbiological

activity if any anomaly occurs.

b. Every time that the digester is emptied from zero, it needs some days for filling all up

and achieving the desired biogas production parameters. The bacteria in charge of

decomposing the mix needs to be controlled while they appear, and that requires

sensors, monitoring and time. If every complete cycle the all the coproducts and biogas

are extracted emptying the tank, the biogas production would be constantly interrupted,

and so the biogas yield.

c. To store all the manure required to fill up every cycle from zero, enormous tanks should

be added, tanks that won’t be necessary (not so big) if manure and biomass is slowly

introduced and coproducts taken out and stored. Controlling the feeding of mix into the

digester allows optimizing the biogas yield.

d. If the mix of manure and biomass it’s introduced every hour into the biodigester, there

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would be less thermal requirements for heating the mix up to 37 ºC, since manure has

high temperature when going out from the cow/pig’s body.

Clearly, emptying everything one each cycle ends is a nonsense. The biodigester would only

be emptied for the reasons explained at the end of this section. However, it must be studied

which is the staying time of all the amount of mix introduced hourly, because each quantity

introduced makes its own cycle during the co-digestion. Following the curve described in Fig.

5.4 explained previously, the first 20 days of digestion are the where the vast majority of the

total CH4 is generated. Actually, the article [26] recommends to have 36 days per cycle to

ensure the desired quality of the biogas (for a mix of manure and biomass similar to the

expected one), leading to the results on the proportions of each molecule constituting the

biogas shown at Table 5.7. The main idea is that if the reaction is maintained at the required

conditions for 79 days – coinciding with the periods that distributes the wastes/resources

perfectly in the volumetric capacity of the pool – the last 43 days only a very small fraction of

new CH4 would be added to the existing biogas: Meaning a waste of energy.

Besides, adding a fraction of mix every hour or day lapse has a special characteristic; the new

manure and biomass added each hour would have a cycle of 36 days until the solid part is

sedimented on the bottom of the digester and extracted, and while this happens the biogas

production would follow a biogas production cycle of 36 days [35].

Thereupon, the solution found is the following: Combine the idea of the cyclic production

periods of the 2nd option but doing it so as it would have been done in the 1st option. In other

words, a small fraction of manure and biogas are going to be added hourly to the digester, but

for each specific amount of mix added a co-digestion cycle of 36 days will take place. In this

way, the anaerobic digester won’t interrupt its activity at any moment except for maintenance

issues. There always would be constant inputs (manure, maize and inoculum) and outputs

(biogas and coproducts obtained at the end of each co-digestion process). As a matter of a

fact, the bacteria population – in charge of doing the anaerobic digestion – inside the

biodigester can be maintained almost constant, stabilizing the biogas production to the optimal

one. It is really important trying to not stop the co-digestion unless it is strictly necessary,

otherwise, recover the bacterial activity achieved at optimal biogas production yields would

require some time.

The idea, to simplify the calculations, is that there would be inside the biodigester many co-

digestion cycles happening at the same time; all of them lasting 36 days but separated

between them by a time lapse equal to the difference of time at which they were introduced in

the biodigester. I.e., if a specific weigh of manure and biomass was introduced the 1st of


January at 13:00 pm and another weight was introduced the 15th of January at 18:00 pm, the

first weight would end its cycle the 6th of February at 13:00 pm and the second one the 20th of

February at 18:00 pm.

Another important parameter to consider is, with the existing infrastructure, finding which of

the already existing facilities of Can Barrina can be used (to decrease the initial investment). It

was already commented that in the EGS proposed in this project the anaerobic digester (or

simply biodigester) would be installed by adapting the already existing pool number 3, which

has a capacity of 1189,67 m3 that are currently used for storing the slurry of cows and pigs.

This decision is made because if the liquid manure is now used in its totality for producing

biogas, pools number 1, 2 and 3 would no longer have a clear purpose – at least not the one

they used to have. Since pool number 3 is the largest one by far, it seems logic to transform

this structure in the biodigester (remember that it was shown in Fig. 4.10).

The dimensions of that pool are approximately 11x12x9 m – 1188 m3, which are in reality

1189,67 m3 – being 11 m of length, 12 m of longitude and 9 m of depth. Eventually, this can

be estimated as the maximum amount of manure plus biomass being treated inside the

biodigester if this volume is taken.

It is also known that the total volume of the mix of manure, maize and inoculum is equal to

5465,5 m3/year. This means that distributing equally this volume along the year using this

capacity; 4,6 filling cycles can be made each year (with 1188 m3 of slurry and biomass mix in

each cycle). This would mean that every 79 days all the volume of the digester would have

been replaced in its totality by new feed. Nevertheless, the digester size that offers the optimal

efficiency would be always the smallest one that allows the complete co-digestion of the mix

entered, because:

• A smaller digester has fewer thermal losses by conduction and convection with the soil

(if undergrounded) and air. Then there would be saving in the heat exchanger that

maintains the co-digestion temperature.

• Smaller motors would be needed to agitate constantly the manure and biomass mix.

• The monitoring and control are easier, as well as its flexibility.

If cycles of 36 days are desired the complete mix’s replacement (of all the volume of the

digester) would require a minimum volume of 352,4 m3. Nonetheless, after looking the volume

of many exiting digesters compiled in the “Instituto para la Diversificación y Ahorro de Energía”

(IDEA), recommends always oversizing the biodigester elongating the staying time of each

portion of mix added every hour to maximize the biogas extracted from it [43]. In all the existing

plants presented at [43], the volume of the digester augments in the other of 277,7 m3 per each

1000 m3 of manure introduced per year. With Can Barrina’s manure the optimal size would be

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then 1008,66 m3. Since is already constructed, it is proposed to leave that volume intact. If not,

the expenses for adapting the existing facility to the optimal one could be higher than the

savings in terms of thermal losses gained for that small extra volume. Actually, there is a

simpler solution that is filling the pool just 1008,66 m3 from the available 1188 m3 – besides,

there must be space for the biogas produced. The biogas would be placed (thanks to its lower

density) at the top of the digester; so, a “calotte” or “roof” must by sized too.

To sum up, the expected design of the anaerobic digester would be then based of the tank

and “calotte” where the gas and the wastes/resources are entered (as well as its insulation

layers), all the valves and pumps that control the fluids and gases flows (biogas output), the

heat exchanger used to maintain the inlet temperature at 37 ºC, electrical devices such as

sensors to monitor the parameters, actuators and the mixers which constantly stir up the mix

and the entering and exit tunnels (from which mix of manure, maize and inoculum can be

added and solid fertilizers sedimented at the bottom can be extracted). The schematic of a

common anaerobic digester, similar to the expected one, is shown in Fig. 5.9.

Fig. 5.9. Simplified schematic of the anaerobic digester studied in the article [44]. (Source: [44]).

Also, the amount of biomethane produced per hour or day can also be known using the results

of previous section. It was found out that 237,87 m3/day (9,91 m3/h) of biogas would be

produced. This means, i.e., that every 36 days 8345,58 Nm3 (at atmospheric pressure) are

going to be produced. In terms of how this affects to the sizing of the biodigester’s calotte is

crucial, analysing where the biogas is located while is being formed by the slurry and maize’s

mix in decomposition. In fact, all the anaerobic digesters are characterised for having a calotte


to enclose all the structure and ensuring a perfect insulation of the substances inside the

biodigesters (otherwise there might be leakages). The calotte can also be seen in Fig. 5.9.

Clearly, the dimensions displaced in Fig. 5.9 are different to the ones described previously for

the digester suited for Can Barrina, but there will be many similarities in the design. The last

thing that remains to size is the calotte. An important detail – specially accentuated in next

section when thermal losses are calculated – is that the structure is buried underground.

Currently the pool is buried but completely opened, so after insolating all the concrete walls

and installing the machinery which makes the co-digestion possible, the last step is to build a

“roof” for the digester. The dimensions of the base are known since it is a rectangle of 11x12

m; dimensions of the pool. However, it is necessary to calculate how much volume would be

needed for locating the biogas produced in each cycle to estimate the minimum altitude of that

of that “calotte”, that in Fig. 5.9 is rounded up to 3 m.

It is recommended to have a free space of approximately 40 % of the space available for the

biomass and manure mix, occupied by the biogas while is being produced [44]. This should

ensure not increasing the biogas pressure too much over the atmospheric. This means that if

1008,66 m3 are occupied by the mix 403,46 m3 should be destined for placing the biogas.

Actually, in [45], it is studied how increasing the pressure affects to the biogas properties: And

it is concluded that at higher pressures some characteristics of the biogas produced, such as

the purification and upgrading costs and the concentration of volatile fatty acids, are improved

at larger pressures. Then increasing the pressure inside the digester is not a problem, but

solution opted in this project is maintain the previously calculated volume. It has been decided

to put a calotte of 3 m of altitude from the pool’s level: supposing an extra approximated volume

equal to 313,37 m3 (that would be summed to the 180 m3 of the pool not occupied). To calculate

this volume the following assumption was done:

• The “calotte” is a spherical cap with rectangular base, and in this case h = 3 m, a = 5,5

m (half of mean the mean value between the pool’s longitude and amplitude); and the

volume is V = (pi*a/6)*(3·a^2 + h^2) [46].

Then, the pressure at which the biogas would be in each specific moment can be easily

calculated (as the temperature is maintained constant) using the ideals’ gasses law:

𝑃1·𝑉1

𝑇1=

𝑃2·𝑉2

𝑇2→ 𝑇1 = 𝑇2 → 𝑃2 =

𝑉1·𝑃1

𝑉2→ Where V2 = 493,37 m3 and P1 = 1 atm. V1 is the biogas at 1

atm produced but that hasn’t been extracted from the digester yet.

Then, the dimensions of the biodigester would be:

• A cuboid of 11x12x9 meters with a useful volume of 1188 m3.

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• A “calotte” approximate as a spherical cab with radius longitude equal to 5,5 m and an

altitude of 3 m.

Fig. 5.10 shows a standard EGS based of the biogas production from an anaerobic digester,

in order to see if there would be other elements to be sized a part from the biodigester. In that

drawing is proposed to have and homogenization tank for the manure separated from the

screw charger where the solid biomass is stored and introduced later into the digester. In this

project it is used another system, and it’s a mixing chamber that allows the optimal mixing of

the manure with the solid biomass. All the co-generation unit of Fig. 5.10 corresponds to the

conversion technologies studied later on.

Fig. 5.10. Standard schematic of an EGS based on biogas production. (Source: [42])

A part from the biodigester itself there are two main components that needs to be sized as well

soon or later, that are:

1. The mixing chamber: It is used for chopping the maize and mixing it thanks to the action

of a stirring system based on sharp metal blades. Usually is composed by a cylindrical

tank made of concrete [47]. Its action is essential to make the biogas production

possible, since the manure and biomass mix needs to be mingled as much as possible

to ensure an equal distribution of all the components forming the mix. The sizing of this

chamber is now done.


2. The biogas storage tank: When the biogas is extracted, it needs to be stored

immediately somewhere in order to not losing it. In this case, a metallic tank would be

used but the sizing of it is done in further sections to adapt it to the conversion

technology.

Before entering to the anaerobic digester all the manure and biomass is mixed for a time of 4

h, in the mixing chamber or pre-mixer, and then once this is done a separating membrane is

in charge of accepting the part of the mix that has already been chopped and mixed correctly

and the part that is still in process. This is backed up by a primary and a secondary decanter,

to ensure correct mixing. [47]

The is sized to have a capacity for at least the total volume of manure, maize and inoculum

that would be introduced in half day (then 7,485 m3 that are rounded up to 7,5 m3). In theory,

with an identical input and output flow of manure and biomass and these wastes/resources

already mixed, respectively, the minimum volume should be the one associated to 4 h of

operation (around 2,5 m3). Nonetheless, the system needs to be oversized to avoid problems

if fluctuations occurs or if more amount of mix is desired to be entered into the biodigester. This

choice is even improved after seeing the problem presented in next paragraph, and then some

problems associated to start again the activity can be mitigated by adding more mix in less

time; being able of treating more wastes/resources in less time in the mixing chamber. Fig.

5.11 shows a schematic of the anaerobic digestion process designed for Can Barrina.

To end with this section, an important maintenance that must be done every 3-5 years is

cleaning all the mud sedimented at the bottom of it due to its normal activity. Not cleaning the

digester would lead to an important loss of the volume of the biodigester as well as to important

efficiency losses on the long term. By cleaning the structure every 4 years – obviously when

more times is done the better for the biodigester, but this interval seems realistic since every

cleaning process requires starting again the co-digestion – it can be assumed to maintain its

properties and volumes for biogas production calculations over the years. [48]

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Fig. 5.11. Schematic of the anaerobic digestion process for Can Barrina. (Source: Own).

5.2. Energetic needs of the biodigester

In this section the electrical and thermal losses associated to the operation and maintenance

of the anaerobic digester are studied, with the objective of enabling the energetic balances

with the biogas production and the energetic needs of the farm. Only in this way, choosing the

optimal technology for the conversion biogas-power is possible.

There are some assumptions that were done in other to facilitate the calculations, but that

would require a deeper study in the real installation project of the anaerobic digester (however,

there are out of the scope of these project as in the studied scale they can be considered as

transients):

• The energy consumption is studied as if the biodigester is always working at its nominal

power rates. This means that the transients happening in the first period when the co-

digestion have not already begun and after refilling the biodigester again every 4 years

(after every cleaning period) are not considered to alter the biogas production rate.

Entering in such degree of detail would require a deep analysis of the evolution of the

bacteriological activity in the co-digestion process considered unnecessary for studying

the energetic needs of this biodigester.

• The cow and pig slurry are introduced at the end of each hour after being mixed in the

mixing chamber, and its mass rate can be considered as constant. The flux of biomass

and manure can be regulated by storing both of them in the adequate silage and pools

respectively. If pool 3 is transformed into the anaerobic digester, pools 1 and 2 could

be used for regulating the entrance of manure into the mixing chamber. Nonetheless,


usually in this kind of structures manure is introduced at the same time that is produced

(but this would require studying at which hours the cows produce more or less manure,

as well as their sleeping periods). Then, a constant manure input is assumed.

• Besides, the manures’ temperature when going out from the cows’ and pigs’ body is

around 38,6 ºC, according to the farm’s owner is the cows’ body temperature.

However, after being mixed with maize at 14 ºC and inoculum at 37 ºC ([35]), the

expected temperature without considering losses in the mixing chamber would be

around 25 ºC.

• The maize would be entered in reality at the end of each day in the required amounts.

This means that at the end of each day 620 kg of maize must be introduced to maintain

the optimal biogas production rates (and 98,6 kg of inoculum). Nevertheless, the

calculations are made hourly so it can be assumed that this maize and inoculum are

added each hour at the same time than the liquid manure, being able of calculating

then the hourly thermal and electrical demand as constant.

• If the previous assumptions are accepted, each hour there would be introduced: 407,8

kg of liquid manure, 25,8 kg of maize and 4,1 kg of inoculum (easily obtained by dividing

the amount of each elements involved each year in biogas production, shown in Table

5.6).

Finally – and this is a constraint more than am assumption – only the loads associated to the

biodigester itself are considered in this section. There are other loads associated to the activity

of producing biogas; such as the pumps needed to increase the pressure of the biogas before

storing it, flow controllers for the circulation of liquid manure, other pumps and so on. In other

words, it is only looked for the thermal and electricals loads that occurs in the anaerobic

digester. The other loads are studied later on, separating those that are common

independently of the conversion technology biogas-electricity and those that depends directly

on the technology chosen. On the other hand, there are other loads considered as part of the

biodigester, like the mixing chamber.

5.2.1. Electrical demand

Clearly, the electrical demand would be much lower than the thermal demand in a digester

that must be kept at a constant temperature of 37 ºC. Nevertheless, there are some loads that

are working constantly while the biodigester is working and some others that are activated at

some specific periods. The most important electrical loads would be:

1. An agitation motor of 5 kW; model AquaLimpia5kW [49] (the company AquaLimpia

makes suited agitators in Germany). The power at which is desired to work is at 5 kW

(enough for a volume similar to the one of the proposed digester [43]), supposing

43800 kWh/year of electricity. In Fig. 5.12 it is shown a model from the same company

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similar to the chosen one.

2. A motor of 4 kW; model SIEMENSB3-4kW (catalogue at [50]), to make the chopping

and mixing of all the biomass and manure. The objective is to make the mix adequate

before entering into the biodigester. That motor would work constantly all over the year

considering a maximum volume of 7 m3 (equal to the assumed available space in the

chopping part of the mixing chamber) and a nominal volume of 2,5 m3 (equal to the

manure and biomass mix entered during 4 h). The idea is that the amount entering

each hour is going out from the mixing chamber every 4 h, so at nominal capacity only

2,5 m3 of the mix would be agitated, chopped and correctly mixed by this motor. The

result in electricity required is 35040 kWh/year.

3. Sensors and monitoring devices: The temperature, acidity, input of mix, gas output,

amount of solids appeared after the digestion and their output flow, the pressure inside

the digester, state of the agitation and mixing motors, recollection of manure and so on

require a lot of sensors (thermometers, barometers, pH sensors…). Finding all of them

individually it’s illogical since the energy required by them if compared with the motors

would be insignificant, so a consume of 1200 kWh/year is assumed.

4. A) The mechanical doors that allows the entering of manure into the mixing chamber:

The manure enters in periods of 1 h to the mixing chamber so normally the valve is left

closed and open 48 times per day. There is a 500 W motor ([50]) that is used during

approximately 144 s/day – 3 seconds for opening or closing – leading to an annual

consumption of 7,3 kWh/year. The manure will go down the pipe using the already

existing machinery. Manure is not put constantly into the mixing chamber since maize

and inoculum would be introduced each hour. Like this, the mixing is optimized.

B) The mechanical doors that allows the entering of biomass and inoculum into the

mixing chamber: In this case the 25,8 kg of maize put each hour should be weight and

introduced manually, since they would be coming out from a silage and automatizing

this process might be very expensive (they are a solid, can’t be treated as liquid). The

same happens with inoculum. Mechanical or electrical balances can be used – no

consumption.

C) The mechanical doors that allows the entering of mix into the biodigester: The valve

won’t be left open for a simple reason, to avoid major thermal losses by not closing

hermetically the digester. Then, the mix can be assumed to be introduced hourly every

time that is going out from the mixing chamber. Two identical doors from the ones of

case A) can be assumed with the same working periods (then 14,6 kWh/year).

D) Two identical doors than for case C) are needed to extracting the liquid and the solid


coproducts; same consumption.

5. A 3 kW pump CEA-CA Lowara3kW (catalogue at [51]), activated each hour to transport

the almost liquid mix from the mixing chamber to the biodigester. The mechanical doors

are opened at the same time that the pump starts working, the working time can be

assumed to be equal to 72 s/h (31m3/h can be transported); leading to 525,6 kWh/year.

6. Biogas extractor: model Vortex Air pump SC-4000 4kW (found at [52]). The pump

would be activated every hour few minutes before the entrance of new manure and

biomass. At its nominal capacity the extraction flow is equal to 475 m3/h, and since

every hour 9,65 m3 are generated by the co-digestion process (and thus extracted), it

can be assumed to be working for 73,17 s/h. The annual consumption associated to

this load would be then 712,23 kWh/year.

7. Liquid coproducts extractor (pump). The same pump used for entering the mix can now

be used for extracting the liquid coproducts from the biodigester. In this case the

quantity of liquid coproducts is a 92 % of the entered mix in volume terms, and so the

consumption would be (maintaining a transporting capacity of 31 m3/h). Therefore, the

electricity ascends to 483,552 kWh/year.

8. Solid coproducts extraction (mechanical tape assumed to work at 15 kW). The solid

coproducts that would appear from the co-digestion process would be sedimented, by

the effect of density (they are heavier), at the bottom of the digester. They don’t

suppose a major part of the coproducts created – remember only a 5 % - so they are

not necessarily extracted each hour, and they can be extracted every 20 hours (after

this time their volume it’s equal to the liquid coproducts generated in one hour). The

mechanical tape is assumed to work only for 2 minutes in each cycle of operation.

Then, the energy consumed would be 219 kWh/year.

9. PLC, computer and other monitoring, actuators and controlling devices: Operating a

device like that requires having at least one person looking after all the parameters and

controlling the different parts of the EGS. In example, in the biogas plant of Vila-Sana,

Lleida, one person is working for 3-4 h per day to ensure the correct operation of their

plant [43] (which produces 1.712.000 kWh/year of thermal energy and 1.528.000

kWh/year of electricity). Nonetheless that plant treats a lot more manure and biogas,

so the time spent by the employee in charge of controlling the cycle would be much

larger. In this case, it can be assumed that an employee must destiny at least 2 h per

day to control all the functioning of the biogas production process and the other parts

of the EGS. Approximately, 1 h/day is assumed to be spent in front of a 300 W

computer, associated to a PLC consuming constantly 9,6 W. Lightning is assumed to

be composed by two LED bulbs of 12 W (opened 1 h/day, while working in the

computer). Then 202,356 kWh/year would be associated to that loads.

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Fig. 5.12. An agitation motor from AquaLimpia. (Source: [49])

Probably there would be other loads not considered in this analysis, but they won’t suppose a

significant fraction if compared to the ones already studied. Table 5.9 shows the annual

consumption per device and the total one.

Load Pnominal (kW) Units tworking (h/year) Econs (kWh/year)

Agitation motor digester 5 1 8760 43800

Mixing chamber’s motor 4 1 8760 35040

Sensor & monitoring 0,0136 10 8760 1200

Mech. doors [A), C) and D)] 0,5 5 14,6 36,5

Mix transporting pump 3 1 175,2 525,6

Biogas extractor 4 1 178,05 712,23

Liquid coproduct’s pump 3 1 161,18 483,55

Solid coproduct’s pump 15 1 7,3 219

CPU 0,3 1 365 109,5

PLC 0,0096 1 8760 84,1

Lightning 0,012 2 365 8,76

TOTAL CONSUMPTION 82210,56 kWh

Table 5.9. Electrical loads of the digestion process and associated consumptions. (Source: Own).

5.2.2. Thermal demand

As we it has been remarked in previous section, the estimation of the electrical demand


associated to the biodigester can simply be done by knowing the typical elements existing in

this kind of technology and estimating their operation hours and power usage. However,

calculating the thermal demand is quite more complex since thermal losses from the digester

to the ground and air must be considered, as well as the energy to heat up the manure and

biomass every time that is introduced into the biodigester. Consequently, the overall thermal

demand has been divided in three main groups to facilitate the obtention of results:

1. Energy for heating the manure & biomass mix to up to 37 ºC: This load

corresponds to the energy delivered to the resource/wastes introduced to the digester’s

tank to heat them up every hour. It can be calculated by assuming the thermal

properties of the mix and their entrance temperature (Tin), as the final temperature (37

± 1 ºC) if the volume and mass rates of each component are known.

2. Energy losses by conduction between the digester and the soil: As a

consequence of having the digester undergrounded, some energy would scape by

conduction from the tank – since the inner temperature would be definitely higher than

the soil’s one. To calculate these losses, it must be assumed: The thermal insulation

used by the digester’s walls with the associated thermal conductivities and

thicknesses, as well as the temperature gradient of the soil from 0 to 9 meters in the

farm’s location for each month. The assumption of constant soil’s temperature for all

the days of one month is done.

3. Energy losses by conduction and convection between the calotte and the air:

There is a large surface of the anaerobic digester that is not undergrounded, which

would actually be in direct contact with the air. A fraction of the thermal losses is

expected to be localized in that part of the tank, since convection effects depending on

the wind speed and ambient temperatures must be now considered (in the previous

there are no convection losses since the soil is quiescent). The same air properties

and parameters used for calculating the thermal losses of the milk refrigeration tanks

in section 4.3.2 are going to be used now, adapting the transfer area to the digester’s

one.

Let’s start then by calculating each thermal consumption of the mentioned loads 1, 2 and 3.

1. Energy for heating the manure & biomass mix to up to 37 ºC:

The first thermal consumption is related with the heat needed for heating up the mix (manure,

maize and inoculum mix) from its inlet temperature into the biodigester up to the 37 ºC – at

which it must be to ensure the biomethane production. The calculations involved to obtain

these results are trivial, since the mass of each specific waste/resource introduced each hour

(chopped and mixed by the mixing chamber) is known. Then, it’s just a matter of calculating

the energy delivered to that wastes/resources every hour.

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Eq. 5.6 shows how is calculated the amount of heat (Q) needed to give to all the mass (m) of

a particular element, waste or resource to increment its temperature from their initial

temperature (Ti) to a final one (Tf). Each specific heat (Cp) for each waste/resource indicates

the amount of energy required for incrementing the temperature in 1 K (or ºC).

𝑄 = 𝑚 · 𝐶𝑝 · (𝑇𝑓 − 𝑇𝑖) (Eq. 5.6)

It is also known the mass of manure, maize and inoculum added each time that a new

production cycle is started – every 36 days – and then the amount of energy that must be

added can be obtained by adapting Eq. 5.5 in the following way:

𝑄𝑡𝑜𝑡𝑎𝑙 = 𝑄𝑚𝑎𝑛𝑢𝑟𝑒 + 𝑄𝑚𝑎𝑖𝑧𝑒 + 𝑄𝑖𝑛𝑐𝑢𝑙𝑢𝑚

= 𝑚𝑚𝑎𝑛𝑢𝑟𝑒 · 𝐶𝑝𝑚𝑎𝑛𝑢𝑟𝑒· (𝑇𝑓 − 𝑇𝑖𝑚𝑎𝑛𝑢𝑟𝑒) + 𝑚𝑚𝑎𝑖𝑧𝑒 · 𝐶𝑝𝑚𝑎𝑖𝑧𝑒

· (𝑇𝑓 − 𝑇𝑖𝑚𝑎𝑖𝑧𝑒)

+ 𝑚𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚 · 𝐶𝑝𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚· (𝑇𝑓 − 𝑇𝑖𝑖𝑛𝑜𝑐𝑢𝑙𝑢𝑚)

Some values are known and some assumption were done to resolve the previous energy

balance. For instance, the masses of manure, maize and inoculum per hour would be 407,87

kg, 25,85 kg and 4,11 kg respectively. Then, the “Cp” of maize will depend on its moisture

amount and if is siled or not before entering to the biodigester. As it is the case in this project,

the maize would be put in a silage so this specific heat would be equal to 2,002 kJ·(kg·K)-1

according to [53]. Once this is clear, some assumptions are done:

• The specific heat of the manure is the same as the water one; 4,18 kJ·(kg·K)-1.

• The inlet temperature of all the mix can be considered as 25 ºC (approximately the exit

from the mixing chamber, supposing that this temperature is kept constant). Then, this

temperature is the same for manure, maize and inoculum in the calculations.

• Instead of using one specific heat for the mix, the three of each component are used.

With the previous parameters and assumptions, it is obtained that every hour the total heat

needed is equal to 6,014 kWh, that are going to be distributed homogeneously over the year.

The annual consumption for this load ascends to 52680 kWh. The efficiencies and the energy

consumed to add this energy and the one associated to the previous loads is considered in

the balances for each conversion technology, because this thermal energy would be delivered

in different ways depending on the case.

2. Energy losses by conduction between the digester and the soil:

These losses are calculated by searching first which would be the expected temperature

gradient in the first nine meters of depth in the farm’s location. Actually, Eq. 5.7 shows how is


calculated this value typically, for a specific location. The parameter T(z,t) corresponds to the

temperature given a specific depth (z) and time (t). The other parameters are: The mean

temperature of the soil (Tm; given a depth that there are no seasonal variations any more), the

oscillation of superficial temperature or ambient temperature (As), the gap in days from the first

one (to) and the thermal diffusivity of the soil in m2/day (α). [54]

𝑇(𝑧, 𝑡) = 𝑇𝑚 − 𝐴𝑠𝑒−𝑧·√

𝜋

365 𝛼 · cos [2𝜋

365(𝑡 − 𝑡𝑜 −

𝑧

2√

365

𝜋𝛼)] (Eq. 5.7)

The results to these calculations are taken from a project already done in the village of

Castellbell i el Vilar in the province of Osona, near Manresa (and not so far from the farm’s

location) [55]. Fig. 5.13 shows the evolution of the temperature depending on the depth and

month.

Fig. 5.13. Evolution of the monthly mean temperature of the soil in function of depth. (Source: [55]).

In this way, the mean between all the temperatures recorded from 1 to 9 meters of depth –

shown in Fig. 5.13 – is done; with the idea of obtaining the mean temperature values in the

first 9 meters of the soil, monthly. The results of that calculations are shown in Table 5.10.

Month Tmean (ºC)

January 12,33

February 11,54

March 10,85

April 11,45

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May 12,69

June 14,06

July 15,75

August 16,95

September 17,65

October 16,9

November 15,8

December 13,85

Table 5.10.Mean temperatures in the first 9 meters of depth for each month. (Source: [55]).

It is really interesting to appreciate that in months with hotter temperatures than others the

mean temperature of the soil is lower, and vice versa. This happens since the soil actuates as

a “thermal battery” that has been absorbing the energy of the summer months where ambient

temperature is higher, and then the temperature of the soil of September or October can be

higher than the one of July (even if the ambient temperature is much higher in July). The same

happens in winter, being lower the soil’s temperature in the first 9 meters of depth in May or

June than in November. For this reason, geothermal systems can be used for cooling in

summer and for space heating in winter. Once this has been commented, let’s focus on the

important calculations for obtaining the thermal losses of the anaerobic digestion due to the

conduction of the mix’s elements and the underground.

The next step is to know how the biodigester is insulated, and which layers separates it from

the ground. If the pool number 3 is adapted to become a biodigester, it is proposed to put a

fibre glass layer as a thermal insulator, and a very thin plastic layer to avoid direct contact of

the manure biomass with the thermal insulator. The idea is to allow a long-term operation of

the digester and avoid problems in the cleaning processes of the tank. In fact, the layers are

expected to be (from inner to outer):

• A 6 cm plastic layer made of expanded polystyrene in molded beads, with kp = 0,04

W/(m·K) [19].

• A 10 cm layer of glass fibre as insulating material, with kg = 0,038 W/(m·K) [19].

• An already existing concrete layer of 20 cm, the concrete is made of sand/gravel with

3 oval cores, and then its thermal conductivity is kc = 1 W/(m·K) [19].

Eq. 4.7 would be now used again but applying some changes. Previously, it was used for

obtaining the thermal losses in the milk refrigeration tank, which happens to be cylindrical.

Besides, in that load there were convection losses associated to the air’s temperature and


wind speed, but in this case this convection losses are not considered as this part of the

digester would be undergrounded. Besides, the area of the structure in contact with the soil is

composed by 5 surfaces: all the lateral sides of the cuboid expect the one in the top, so the 4

lateral ones and the bottom surface. It can be considered as 5 plane walls, speaking in

vocabulary of thermodynamics. Eq. 5.8 shows how the “Rtot” for this structure is calculated,

and then Eq. 4.7 can be applied to know the thermal losses by convection, considering in this

case that the outer temperature is the smallest one and the inner the highest (37 ºC). The letter

“L” corresponds to the thickness of each layer that is forming each plane wall.

𝑅𝑡𝑜𝑡 = 𝑅𝑙𝑎𝑡𝑒𝑟𝑎𝑙 + 𝑅𝑙𝑜𝑛𝑔𝑖𝑡𝑢𝑑𝑖𝑛𝑎𝑙 + 𝑅𝑏𝑜𝑡𝑡𝑜𝑚 =1

𝐴𝑡𝑜𝑡𝑎𝑙· (

𝐿𝑝

𝑘𝑝+

𝐿𝑔

𝑘𝑔+

𝐿𝑐

𝑘𝑐) (Eq. 5.8)

The total area would be the sum of all the mentioned surfaces, obtained as follows:

𝐴𝑡𝑜𝑡𝑎𝑙 = 𝐴𝑙𝑎𝑡𝑒𝑟𝑎𝑙 + 𝐴𝑙𝑜𝑛𝑔𝑖𝑡𝑢𝑑𝑖𝑛𝑎𝑙 + 𝐴𝑏𝑜𝑡𝑡𝑜𝑚 = 2 · (11 · 9 + 12 · 9) + 11 · 12 = 546 𝑚2

An important detail on how Eq. 4.7 is used is that the external temperature corresponds in this

case to the soil’s temperature of each month, shown at Table 5.10. Since the energy loss (qr)

is obtained as a power function (W), it can be known the energy lost per hour by multiplying

that result per one – and dividing by 1000 to have it in kWh: Annual losses of 25212,707 kWh.

Fig. 5.14 shows the power lost monthly (considered as constant for each month).

Fig. 5.14. Monthly power thermal losses by conduction digester-soil. (Source: Own).

3. Energy losses by conduction and convection between the “calotte” and the air:

Regarding the last thermal consumption associated to the implementation of the anaerobic

digester, the thermal losses from the inner biogas (at 37 ºC) to the air are also calculated. To

0

500

1000

1500

2000

2500

3000

3500

1 2 3 4 5 6 7 8 9 10 11 12

qr

(W)

month (n#)

Power losses per month

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obtain those results, some assumptions were done in order to facilitate the calculations:

• It was calculated in the section 5.1.5 the volume of that “calotte” assuming that is

spherical cap with rectangular base with h = 3m, a = 5,5 m. In this case, the surface

for that geometrical form is calculated as A = 2π·[(a2+h2)/(2h)]·h = π(a2+h2) = 123,3 m2

[46]. The assumption is that the heat transfer in that spherical cap can be considered

as the same that is would happen in a plane wall of the same transfer area. In other

words, the model of the heat transfer in a sphere is not taken since this would be only

applicable to a full and symmetrical sphere. In this case, the longitude and amplitude

of the rectangle that forms the base are not equal, and neither is the altitude of the

“calotte” in proportion to the expected one for a perfect sphere. Then, making this

assumption simplify a lot the mathematical expressions that would have been required

to obtain if the most realistic model is taken.

• An area of 4,6 m2 is added to the previously calculated 123,3 m2, corresponding to the

10 cm of wall that are not undergrounded. Thus, the transfer area for calculating the

thermal losses with the air is equal to 127,9 m2.

• The convection effects in the inside of the tank can be neglected, since the speed of

the biogas inside the digester is really slow (even if there are recirculating movements

derived from the electric mixers).

Once this is clear, the procedure for obtaining the thermal losses is the same that the one

followed in the losses from the digester to the ground, but in this case to the air. Eq. 4.7 will be

used again but in this case the “Rtot” is calculated following Eq. 5.9, which takes into account

the convection losses in a plane wall (as the assumed one).

𝑅𝑡𝑜𝑡 = 𝑅𝑐𝑜𝑛𝑑𝑢𝑐𝑡𝑖𝑜𝑛𝑡𝑜𝑡𝑎𝑙+ 𝑅𝑐𝑜𝑛𝑣𝑒𝑐𝑡𝑖𝑜𝑛 =

1

𝐴𝑡𝑜𝑡𝑎𝑙′· (

𝐿𝑝

𝑘𝑝+

𝐿𝑔

𝑘𝑔+

𝐿𝑐

𝑘𝑐+

1

ℎ) (Eq. 5.9)

The convection heat transfer coefficient for the air was already calculated in Eq. 4.8, Eq. 4.9,

Eq. 4.10 and Eq. 4.11 for the case of the milk refrigeration tanks; and it would be the same in

the expected location of the biodigester (placed quite near where those tanks are). The value

of “h” is already known for each hour of the year, as well as the air’s temperature. Hence,

applying Eq. 4.7 for each ambient temperature and associated “h” the hourly thermal losses

can be known. Fig. 5.15 shows the total amount of that losses per month.


Fig. 5.15. Monthly energy losses by convection and conduction from digester to air. (Source: Own).

Therefore, the thermal losses for load 3 are equal to 5912,36 kWh/year.

Finally, all the thermal demand of the biodigester is known since in calculations of load 1 it was

obtained the amount of heat needed for heating up all the elements inside the digester from

their respective temperatures to 37 ºC (to make the anaerobic co-digestion process happens

at the beginning of each cycle), and in the calculations of loads 2 and 3 the thermal losses

were found taking into account the external variation conditions and the thermal insulating

layers of the expected biodigester. Then, Fig. 5.16 shows a comparison between the impact

of each thermal load studied and the total thermal consumption; that ascends to 83805,1 kWh

per year.

Fig. 5.16. Impact of the studied Loads 1, 2 and 3 in the total thermal consumption associated to the

biodigester. (source: Own).

0

100

200

300

400

500

600

700

Thermal energy lost per month in load 3 (Wh)

59%28%

13%

PERCENTAGE OF IMPACT IN THE FINAL ENERGY CONSUMPTION PER LOAD

Load 1 Load 2 Load 3

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This means that every year 83805,1 kWh (not including conversion efficiencies and ways for

obtaining them, studied in next section) would be destined to ensure a constant temperature

of 37 ºC inside the biodigester, vital to keep running the biogas production process. The energy

produced in form of biomethane each year by that biodigester ascends to 556.028,7 kWh, so

at least a 15 % of the energy produced in form of biogas each year would be lost to allow that

process to occur.

The thermal needs of the biodigester are shown in a three-dimensional graphic to see the

evolution along the year with detail. To represent it in a clear graphic the mean thermal

consumption of each month was obtained for all the hours of that month (by summing all the

hourly thermal consumptions of each month and dividing this per the days of each specific

month); resulting in 1 standard day for each month with the hourly evolution of the biodigester’s

thermal demand. Fig. 5.17 shows the mentioned evolution.

Fig. 5.17. Daily evolution of biodigester’s mean thermal demand of each month. (Source: Own).

In next sections, all the calculations made until now would be optimised to find the best

technology to transform the produced biogas into the electricity and heat needed to run the

farm and to make front to the new electrical and thermal – especially thermal – demands

associated to the biodigester itself.


6. Biogas upgrading

At the beginning of this project it was not contemplated to dedicate a singular section to this

matter – biogas upgrading – since it could seem that the biogas can be directly used after

being produced in the anaerobic digester. The reality differs a lot from that, since the impurities

and undesired gases that appears in the biogas (Table 5.7) affect to the performance and to

the life cycle of the conversion technologies. This section has been placed before presenting

the conversion technologies, because this project is ordered in the steps that the biogas would

follow from its creation (coming from biomass and cattle manure) to its final conversion into

electricity and heat power. Before this final transformation into useful energy, the raw biogas

has been found to need a purification for the motives now argued. However, the problems that

impurities can cause to the conversion technologies are the main reason for upgrading this

biomethane, so these technologies are introduced:

1) SOFC: The first conversion technology analysed is the Solid Oxide Fuel Cell, which

can work at medium or high temperature (depending on the model) and use an input

gas – such as biogas, syngas, natural gas and so on – to produce electricity and heat.

In conversion works thanks to the application of chemical reactions and the presence

of an anode and a cathode for holding up these reactions.

2) A gas cycle: The second conversion technology analysed is a typical gas boiler which

feeds a gas cycle for producing electricity (gas turbine) and heat. The technology used

in that case is the most extended one and it would work as a typical natural gas boiler,

but in this case with biogas – which we know beforehand that would need to be

upgraded, since current engines only work with high-level of purity of the CH4.

In next section the conversion technologies are deeply studied and size, but what matters now

is to determine first if the biogas should be upgraded and up to with what level of purity in each

of the studied systems. Once this is known, a sizing and explanation of the upgrading systems

is presented.

6.1. Biogas quality requirements

In this part it is studied if the biogas should or not be upgraded and why, for both conversion

technologies.

6.1.1. SOFC biogas quality requirements

In the case of the SOFC chosen as the fuel cell that suits better to Can Barrina’s for the reasons

explained in further sections; the device works better, improves its performance or just its able

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to work (without suffering irreversible damages) for a specific composition of the biogas. The

idea is to assess if there are some components of the expected mix of biogas that could

jeopardize the correct functioning of the SOFC. If this happens, there would a real necessity

of upgrading the resultant biogas to ensure the optimal operation of the conversion technology.

In order to do so, a deep research into the exiting articles of SOFC operation was carried out,

looking for the effects of impurities in its performance. For example in the article Operation of

solid oxide fuel cell on biomass product gas with tar levels > 10 g Nm-3 [56], it is exposed that

thanks to the high temperatures reached in the normal operation of a SOFC (that can oscillate

from 600 – 1000 ºC), a gaseous mixture with H2, CO, CH4, CO2, N2 and H2O won’t hurt directly

the operation of the fuel cell. These components usually appear in the thermochemical

gasification of biomass and manure in various proportions depending on the technique that is

used. In this case all of them except the water are present in Table 5.7. The SOFC can cope

with these components without supposing an imminent risk to its functioning. [56]

On the other hand, in raw biogas produced by the co-digestion process there could be traces

of H2S, NH3, HCN, corrosive volatile alkali or metal particles that can be dangerous for the

device [56]. In our case, it is expected to be at east a 0,4% of H2S in the raw biogas

composition, and actually it has been reported by many articles as one of the most poisonous

impurities for SOFC at levels higher than 1 ppm [56], [57]. The main problem associated to

H2S is related with a degradation of the nickel contained inside the SOFC anodes, even if that

type of fuel cell is the most robust because it has a high “tolerance towards the other trace

constituents of biomass derived from product gas” [56]. Regarding the effects on the anode,

they could be reduced if nickel (Ni) was not used as anode, but the most satisfactory results

were obtained for the anodes composed of [58], [59]:

• Ni-CGO: This anode is typically composed by a 60:40 wt.% of Ni and Ce0.9Gd0.1O1.95

(CGO) cement [58]. The electrolyte would be then a CGO-10 cement. There is also

the Ni and a gadolium-doped ceria anode (GDC) without the Oxigen, (Ni-GDC) [56].

• Ni/YSZ: This anode is composed by Ni and yttria-stabilized zirconia (YSZ) cement

anode, with a YSZ electrolyte pellet [59].

The idea is we can’t get rid of the Ni being present in the SOFC, since that structures are the

most efficient ones that gives higher electricity production yields. Then, the H2S would surely

suppose a problem so it must be separated from the raw biogas after these is produced in the

co-digestion process. To do so, there are multiple Gas Cleaning Units (GCU) – or Gas

Conditioning Units – that enables the removal contaminants ensuring the proper quality levels

of the biogas entering into the SOFC.


Then, another problem is the effect of carbon molecules without hydrogen (CO, CO2) that could

generate depositions in the Ni-based catalysts. To avoid this deposition, humidify the SOFC

generating steam that creates a high molar ratio of steam-to-carbon, lengthening the fuel cell

live but on contrary lowering down its efficiency. Thus, it is decided to not treat these carbon-

based molecules, specially the CO which the SOFC can take advantage the “major product

gas combustible contents”, according to [56]. It is not considered necessary entering in such

deep detail, but the optimal temperature for SOFC operation are those around 850-920 ºC for

the reasons mentioned later on. At those temperatures the electrochemical oxidation of H2 and

CO are less affected by the presence of impurities. [56]

Therefore, in next section the GCU chosen if the conversion technology chosen is the SOFC

is studied. Now, let’s see the quality requirements that would be expected if the biogas is

desired to be burned in a boiler.

6.1.2. Gas cycle biogas quality requirements

On the other hand, the other alternative to transform the biogas into electricity is a boiler

associated to a gas cycle and a generator. The quality-levels of the input gas into these devices

are well-kwon and extended around the world from many years now (since NG is used for

many energy generations purposes in boilers, and the NG grid is widely extended so is an

affordable and reliable fuel).

So, in a gas boiler the Heat Transport Fluid (HTF) is typically water or air, and then this HTF is

heated up thanks to the combustion of the input gas (syngas, reformed biogas, NG, butane…).

Both the feedwater/air and the gas used must have a minimum quality levels to avoid damages

in the entire system. Those damages can affect its performance – basically reducing its

efficiency – they can affect the boiler’s life cycle or, even worse, they can end with boiler or

system leaks or breakage. In this section only the input gas used to make the combustion are

assessed.

The overall conversion efficiency of the raw biogas goes typically from 10-16 % if it is not

treated before being entered into the boiler [60] – considering that the CH4 percentage variates

from 50-70 % of the total volume of the biogas and the CO2 around 30-40 % of that volume.

This efficiency rates are much lower to those expected from a typical gas turbine (GT) with an

efficiency that goes around 39 % for large turbines and up to 58 % for Combined Cycle Gas

Turbines [60] – which takes profit of the electricity and the thermal energy the same way. The

idea is that removing everything expect the desired methane part of the biogas derives in

higher efficiency rates in the GT, and thus removing the undesired impurities and specially the

CO2 must be done to boost the GT efficiency.

On the other hand, H2S would also be very dangerous since in the combustion of the biogas it

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would actuate as a corrosive agent and also would generate hazardous compounds [61]. Its

removal is compulsory before burning the biogas. Then, all the impurities as well as the CO2

should be removed from the biogas, incrementing the CH4 content present in the biogas, and

how this is done is explained in next section.

6.2. Upgrading technology

Once the expected molecules that should be removed from the biogas for each conversion

technology are known, the next step is to see how those molecules (impurities, pollutants or

just undesired particles) are going to be removed.

This is important since it would directly affect the capital investment costs of each EGS studied,

and would take a clear importance in the economic analysis and the final comparison between

the studied systems.

6.2.1. GCU selected for the SOFC alternative

For the reasons commented before, the impurities that affect the correct functioning of the

SOFCs must be taken away before entering in the device. The GCU is in charge of doing this

labour, and the first step is always to filter the microscopic particles that can be suspended in

small quantities in the biogas (not even considered as a percentage of the biogas composition).

This is usually done in two steps [56]:

1) Hot gas cyclone: Cyclone separators have been used for more than 100 years, and

there are still used for many industrial processes needing gas cleaning. They are

simple, but at the same time robust, economic, durable, easy to install and without

moving parts. Their functioning is simple, and the explanation of [62] is followed: “The

gas flow is forced into downward spiral simple because o cyclone’s shape and

tangential entry”. The idea is that with the centrifugal force and the inertia of all the gas

the little particles (with higher weight) “move outward, collide with the outer wall, and

then slide downward to the bottom of the device”. When the gas reaches almost the

bottom of the cyclone the gas “reserves its downward spiral and moves upward in a

smaller inner spiral”. Then there is an exit tube for the gas at the top of the cyclone and

a sealed-pipe by a rotary or flapper valve at the bottom the control the exit of the

particles [62]. Fig. 6.1 a) shows an image of the cyclone.

2) Sinter metal filter candle: Nonetheless there are some microscopic particles that the

cyclone cannot get rid of, since they are too small for being derived to the bottom of


the device. These particles can have lengths from 1 to 1000 μm [63], so the used way

to subtract those impurities from the gas is a combination of filters put in series, which

at the end results in a gas without little particles. The hot gas cyclone cannot be directly

substituted by this filter, since the larger particles are separated there – and otherwise

the filter would be damaged. Fig. 6.1 b) shows a typical sinter metal filter candle.

Fig. 6.1. Particles removal unit: a) Hot gas cyclone (Source: [64]). b) Separation membrane of a sinter

metal filter candle (Source: [63]).

The next step is to increase the biogas pressure with an ejector pump – using pressurized

steam – to overcome pressure losses in the next steps: the trap beds. The idea is that each

trap bed is used to get rid of one specific undesired particle. In the experiment of the article

[56], there was first the chlorine removal bed (using sodium promoted alumina), then the H2S

removal bed (using ZnO and ZnO/CuO beds) and finally the tar reformer (that could be by-

passed allowing the tar to reach the SOFC; otherwise dolomite and NiO beds are used) [56].

The idea is to make the pressurized gas pass thought these beds and the undesired

components would be trapped by them. In our case, the chlorine bed could be neglected, but

the ZnO and CuO beds must be used to remove H2S and the Dolomite and NiO beds can be

left to ensure no tar in the fuel cell. The gas quality must be monitored to ensure the expected

quality parameters before entering in the SOFC.

The functioning of all the system used in the previously mentioned system (of the experiment

carried out in [56]), is shown per parts in Fig. 6.2 – where a) is the gasifier, b) is the GCU and

c) is the SOFC.

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Fig. 6.2. Schematic of the biogas production and conversion system of the experiment of article [56].

(Source: [56]).

To make the calculations of the electricity produced in next sections the CH4 exiting within the

biogas composition is used, so it is assumed that there won’t be methane losses in the GCU

before entering into the SOFC.

6.2.2. GCU selected for the gas cycle alternative

The GCU selected for the gas cycle has been decided to be identical to the one proposed for

the SOFC – removing small solid particles in the hot gas cyclone and the sinter metal filter

candle, then increasing the pressure of the biogas in the ejector pump and finally removing

H2S and tar in the trap beds; as shown in Fig. 6.2 b) – but adding a specific system for removing

the CO2.


There are different ways of removing the CO2 from the biogas, and the main are [65], [66]:

• Absorption: Water, chemical and physical scrubbing are the most used.

• Adsorption: Pressure Swing Adsorption is the most used by far.

• Cryogenic distillation

• Membrane separation technologies: Polymeric membranes, composite carbon

membranes…

One of the less extended one is the use of specific type of membranes, and it for this reason

it has been discarded as the CO2 separation method – it just suppose a 2 % of the market

share [65]. Cryogenic distillation is more used, but the most extended methods are CO2

absorption and adsorption by far. In the article [61]; it was studied a method for removing the

CO2 and the H2S at the same time in a packed column reactor, but they conclude that this

method has a great wear and a wastage of its efficiency over the time, and the technology

would be then more expensive. In fact, [66] highlights the importance of removing the H2S

before entering in the CO2 removal unit, because otherwise there would be problems in

absorption and adsorption techniques.

The main idea is to fins the most economic method that ensures the correct removal of the

carbon dioxide, and this would depend on the size of the plant since today there are GCU sets

commercially available for standardized upgrading plants (for capacities lower than 250 Nm3/h

up to plants that produce more than 2000 Nm3/h of biogas) [66]. Fig. 6.3 shows the cost per

CO2 removal technology depending on the amount of biogas generated, in this case, in the

anaerobic digester.

Fig. 6.3. Cost of CO2 removal technology depending of the biogas generated. (Source: [66]).

Since the amount of biogas produced in Can Barrina was approximated to be around 9,66

Nm3/h, the scale of the plant is much lower to the values here treated, and the most economic

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offer is recommended to be taken. Due to the availability of information of prices from

manufactures is limited, it has been decided to use a chemical (or amine) scrubber from MT-

Energie as the cheapest solution observed in Fig. 6.3, which is actually the cheapest solution

for small-scale systems.

The bases of the absorption methods are briefly commented. In this method the raw biogas

“meets a counter flow of liquid in a column which is filled with a plastic packing” and the idea

is “to increase the area of contact between the gas and the liquid phase”, according to [66].

The main principle is that CO2 is more soluble than CH4, so “the liquid leaving the column will

thus contain increased concentration of carbon dioxide while the gas leaving the column will

have an increased concentration of methane”, same reference again [66].

Once this is clear, in the case of the chemical scrubbing amine solutions are used in order to

not only absorb directly the CO2 in the liquid going in counter flow with the biogas, but to make

a chemical reaction with the amine solution too. In other words, the carbon dioxide exiting in

the raw biogas would be absorbed by the liquid (while the methane part not due to its lower

solubility) and at the same part this CO2 would react with the amine exiting in the liquid (see

Fig. 6.4). Besides, the chemical reaction is “strongly selective” making the methane lost be <

0,1% [66]. In fact, the methane losses in the GCU are neglected in this project.

Fig. 6.4. Typical functioning of a chemical (or amine) scrubber. (Source: [67])


Once the liquid has absorbed the CO2 part of it is evaporated and then replaced, while the part

where CO2 “is chemically bound is regenerated by heating”. The two amine compounds used

are Mono Ethanol Amine and Di-Methyl Ethanol Amine. This book of the IEA Bionergy – called

Biogas upgrading technologies – development and innovations – remarks again that there

would be a tremendous problem if H2S was not extracted before entering in the chemical

scrubber, because it would be absorbed by the amine solution and “higher temperatures would

be needed for the regeneration”. [66]

At the end, the removal of CO2 generates a clear upgrading of the biogas since its energy

density is drastically increased. Table 6.1 shows a comparison between different methods,

and the quality of the expected biogas at the end of the process. The most important parameter

is that the biogas can be expected to have now a methane content of 99 %, so the heating

values of the upgraded biogas can now be calculated.

Table 6.1. Comparison between different scrubbing methods and Pressure Swing Adsorption (PSA)

method. (Source: [66]).

The energetic needs of both GCU – for the SOFC and for the upgrading needed in the gas

cycle – are approximated for performing the economic analysis later on.

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7. Applicable conversion technologies

In this section the final definition of whole EGS is carried out. At this point, all the installations

needed to transform the cattle manure and biomass into raw biogas and then upgrade it have

been studied. Besides, the thermal and electrical demands of the farm have been also studied

to know them per each hour of a standard year. Hence, the last point is to study how this

upgraded biogas can be transformed into electricity and heat, and which options are better

technically – the economic comparison is made in section 8.

7.1. Introduction to the alternatives assessed

Then, as introduced in the previous point, the two base conversion technologies assessed, to

transform the biogas into electricity and heat, are:

• SOFC: Its maximum conversion efficiency is expected to be around 90% [68] – usually

around 50% is thermal and 40% electrical [69] – depending on the configuration used.

Actually, for power generation there are a wide range of configurations using a SOFC,

as presented later on.

• Gas cycle: Combined Heat and Power (CHP) plants and Combined Cycle Power

Plants (CCPP) run by gas usually have efficiencies of 39% and 55 % respectively.

Nonetheless, these values varieties depending on the plant configuration and size. In

this case, it is looked for a small size CHP, (because introducing a Brayton cycle and

a Rankine one which takes profit of the exhaust gases of the first would be pointless in

a small-scale power generation unit). The alternatives are also assessed later on.

Nonetheless, many variations in the disposition and elements which compose the conversion

system can be studied and added. In this section it would be analysed why these were the

chosen methods for energy conversion, presenting alternatives fuel cells to the SOFC and

other kind of thermal cycles that could have been used instead of a gas cycle with a GT.

7.1.1. Conversion using a fuel cell

The market of fuel cells is limited to the already existing technologies, and not all the fuel cells

can work with biogas as the input reactant for its internal processes. In fact, the main fuel cells

available right now are listed on Table 7.1 – where the electrolyte typically used, their common

working temperature and the fuels that each fuel cell type can used are listed too.


Fuel Cell Type Acronym Typical electrolyte Temp. (ºC) Fuel

Solid Oxide SOFC Zirconia doped with Y2O3 ~ 800 NG/H2 …

Molten Carbonate MCFC Na2CO3 + K2CO3 ~ 600 NG/H2…

Phosphoric Acid PAFC H3PO4 ~ 200 H2

Proton Exchange Membrane PEMFC Polymer membrane ~ 50-120 H2

Direct Methanol DMFC Polymer membrane ~ 50 - 90 CH3OH

Alkaline AFC NaOH + KOH ~ 100 - 200 H2

Table 7.1. Type of fuel cells, acronym, typical electrolyte, typical working temperature and usable

fuels. (Source: [70]).

Only watching which fuels can be used in each fuel cell type, SOFC and MCFC are the unique

options that can work with biogas. As a matter of a fact, these fuel cells are labelled in the high-

temperature group; specially used in stationary applications in buildings and large facilities.

This suppose some tremendous advantages such as the higher overall efficiencies performed

in fuel cells – not necessarily electrical, but due to its internal high temperatures thermal energy

can also be a final/usable energy product. Moreover, the high temperatures also enables the

substitution of Platinum catalysts – used in other fuel cells such as PEMFC, PAFC and DMFC

– for Nickel ones, cheapening the catalyst price [70].

Then, the two valued alternatives for transforming the biogas into electricity and heat were

SOFC and MCFC. In this project we are seeking for the best EGS as possible, technically and

(specially) economically. One way of optimizing the overall efficiency of high temperature fuel

cells that has gained popularity among these kind of installations – with CHP purposes – is

hybridising the conversion system. SOFC and MCFC can be integrated as a part of a hybrid

cycle; adding a GT, a steam turbine or both [71].

Consequently, in this project the alternative of just installing the SOFC/MCFC is studied as

well as the possibility of adding a GT – analysing the changes that this would trigger in the

overall efficiency of the system, and in the economic plane. Therefore, the choice was made

by just taking into account the one which offers higher electrical efficiencies by itself, but it was

conditioned by the one that can be accoupled easily/securely in a hybrid cycle.

On the one hand, the article Comparison of Molten and Solid Oxide Fuel Cells for Integration

in a Hybrid System for Cogeneration or Tri-generation [71], compared the individual efficiency

of both fuel cells without being part of a hybrid cycle. For a 20 MW MCFC the efficiency of the

fuel cell was 2 % higher than the efficiency of a 20 MW tubular SOFC. The working conditions

where 675 ºC at atmospheric pressure for the MCFC and 980 ºC and also atmospheric

pressure for the SOFC.

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Then, in the cited experiment it was compared the efficiency of two hybrid cycles being one of

them based on the mentioned MCFC another based on the mentioned SOFC. The conclusions

they reached is that at 1 atm the efficiency of the hybrid cycle with the MCFC was 2,2 % higher,

but this changes if the pressure of both processes was increased up to 9 atm. With the

increment of pressure, the efficiency of the SOFC-based hybrid cycle became higher than the

one of the MCFC-based system at 1 atm. This system was not pressurized up to 9 atm

because “pressurized operation is problematic for the MCFC due to increased cathode

corrosion leading to cathode dissolution as well as sealant and interconnection problems” [71].

They reached the conclusion that in a hybrid configuration the SOFC can be more efficient,

while from 1 to 6 atm the individual efficiency of the MCFC can be higher.

The previously commented corrosion problems of the MCFC have been minified in the lasts

years, controlling the corrosive nature of the electrolyte to achieve more durable lifetimes [72].

In fact, the article Energy and economic comparison of SOFC-GT, MCFC-GT and SOFC-

MCFC-GT hybrid systems found out which was the most convenient system for plants of the

same power capacity for the fuel cell prices of 2018 [73]. They found out that, once the

corrosion problems reported in [71] are solved, the MCFC-GT are the ones offering higher

electrical and thermal efficiencies, followed by the SOFC-MCFC-GT and finally the SOFC-GT.

The main drawback is that systems with MCFC are quite more expensive (see Fig. 7.1). [73]

Fig. 7.1. Variation of efficiency and annualized costs with current density. (Source: [73]).


Fig. 7.1 shows that when the current density increases in the fuel cell the efficiency goes down,

and this happens since there are more electric losses [73]. Having a lower current density for

the same nominal power of the fuel cell – SOFC or MCFC independently – requires a higher

investment in the technology, so it is more expensive. The costs are all calculated on the base

of a 3 MWe hybrid system. Obviously, the quality of the fuel cell must be chosen by the person

who is interested in making the investment, and the electricity production would be affected

then. The efficiencies of Fig. 7.1 are all electrical, but in counterpart when electrical efficiency

is increased by adding GT the thermal one is decreased (since thermal energy of the fuel cell

is used to produce electricity).

Since the electrical efficiency of the three systems compared did not change so much – a

maximum of a 4 % approximately between the best system (MCFC-GT) and the “worst”

(SOFC-GT) – but the prices are really affected, the SOFC was chosen as the best alternative

for Can Barrina. It is chosen for the economic criteria:

• For low current densities (high efficiencies) the SOFC-GT system is around 25 %

cheaper than the MCFC-GT system.

• For high current densities (lower efficiencies) the SOFC-GT system costs less than

the half of the MCFC-GT system.

Following this criterion, the economic savings have more weigh in the final decision than the

efficiency gains, and for this reason the SOFC was chosen as the fuel cell technology. The

technical functioning of the system is presented in the following sections, where each

alternative is analysed technically. In the next point it is analysed why a gas cycle was

considered instead of other options working with the direct biogas combustion.

7.1.2. Conversion using a gas cycle

The most efficient conventional way of obtaining electricity from NG – or in this case CH4 with

99 % purity; after being upgraded in the GCU explained in the previous section – is achieved

by mixing this gas with a stream of air and then burning the mix [74]. The idea is to make a

combustion process (with excess air) generating an expansion of the mix in the gas turbine,

transforming the CH4 chemical energy into rotational energy that is converted into electricity

by the action of a synchronous generator. Nevertheless, after the combustion process not all

the energy is transformed into electricity by the turbine, because the exit hot gases have a high

enthalpy and can be used as thermal energy.

In fact, those hot gases are typically used by the heat recovery steam generators to heat up

water in a secondary cycle – being the primary cycle the gas cycle – that generates more

electricity in a steam turbine [75]. This is the principle behind CCPP, which combines a Brayton

cycle and a Rankine cycle producing electricity and heat (and cool in some cases, having tri-

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generation). The exhaust gases can be at a different range of temperatures, depending on the

pressure gap between the input and the output gasses in the gas turbine; there is always a

compressor that pressurize the input air mixed with the gas, which would be at that same

pressure. After the expansion takes place and the gasses are used to move the turbine there

is a pressure, and a temperature, drop. The result is a wide range of temperature variation of

the exhaust gases depending on this pressure drop. However, the values go typically from 450

ºC to 600 ºC. The exhaust temperature is controlled if the plant is a CCPP, to maximize the

plant efficiency after using the exhaust gases to heat up the water in the heat recovery steam

generator (having a Rankine cycle).

Burning the gas in a boiler to heat up water making a Rankine cycle (associated to a steam

turbine) would suppose having lower efficiency than the ones expected from the gas cycle

proposed. Then, the only incognita is if a heat steam recovery system should be used for Can

Barrina’s necessities: And the answer is no, for the following reasons:

• The Energy Information Administration of U.S. Government (EIA) estimates a capital

expenses of 389 US$/kW installed in simple gas cycle plants and 500-550 US$/kW

installed for CCPP. Then, even if the electrical efficiency is widely improved the cost

would increase in a 23-30 %.

• With the implementation of the anaerobic digester the expected thermal consumption

of the farm would increase drastically, new 83805,1 kWh/year would be required by

the biodigester. Consequently, it would not be intelligent using the exhaust gasses of

the gas cycle for heating water in a Rankine cycle for producing more electricity:

Because those gases could be used directly in the anaerobic digester’s heat exchanger

to provide the heat required by the co-digestion process to maintain 37 ºC. In fact, in

next section is analysed if in that context the energy of the exhaust gases would be

enough to cover this demand – otherwise an auxiliary boiler would be needed.

• The biogas power produced constantly (assuming constant production) would be

around 63,47 kW. Obviously, CCPP technologies are only economically feasible for

larger plants of the MW-GW order.

The main reason for choosing just the gas cycle is for the second reason listed above, and it

is that is the technology that fits better with the farm’s necessities. The most important thing is

finding the technology that adapts better to the costumer of this project, technically and

economically.

At the end, the three studied alternatives would be:


1. SOFC: A single fuel cell would transform the biogas into electricity

2. Gas cycle: The biomethane (after upgrading) would be transformed into electricity

using a generator accoupled to a GT, taking profit of CH4 combustion.

3. SOFC-GT: The fuel cell has a gas turbine that works with the exhaust gasses released

by the SOFC, increasing its electrical efficiency.

In the following three sections these alternatives are studied one by one. In each of them, the

technology functioning is presented, as well as the conversion efficiencies of the technology

and its sizing criteria – considering the hourly thermal and electrical consumption and the

biogas generation, calculated in previous points. At the end, the difference between the

demand and the energy production (thermal and electrical) can be made, assessing if auxiliary

units might be implemented or, on the other hand, excess energy can be used for other

purposes or sold – in case of electricity it can be injected into the electric grid, but thermal

energy is difficult to be sold as district heating considering the farm’s location; building the

transportation pipelines would be inefficient (almost all the heat would be lost) and expensive.

7.2. Alternative 1: SOFC

7.2.1. Description of SOFC

The first alternative studied is the SOFC without any complement, just the components of the

fuel cell itself. The idea is to produce electricity and heat simultaneously, using the exhaust

gases (and warm water) of the SOFC as thermal energy. Therefore, the first point should be

describing the functioning of this kind of fuel cell, then size the device to adapt to the

characteristics of the farm and finally finding a SOFC model with its efficiencies and calculate

the energy that could be generated using the biogas.

Let’s start describing the structure of the SOFC. Typically, this fuel cell is composed by [70]:

• Anode: Y2O3 + stabilized ZrO2

• Electrolyte: YSZ (yttria-stabilized zirconia)

• Cathode: LSM (La0.8Sr0.2MnO3)

• Catalyst: Ni (high temperature of operation avoids using Platinum).

The SOFC can use NG directly from the gas grid as well as many equivalent gases (syngas,

biogas, pure methane…), working in a range of temperatures from 500 ºC to 1000 ºC. Some

studies such as [56] suggest that the optimal temperature range of a SOFC would be 850-920

ºC, while other articles highlight that they find the maximum efficiency of the studied SOFC at

800 ºC [76]. In fact, this last article says that 800 ºC is the most used SOFC operation

temperature. Another highlighted affectation of the temperature is the cell materials

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degradation depending on the temperature and the gas mix (having CO2 as it would happen,

the lifetime of the SOFC can be reduced in some hours, but not drastically), having a specific

range of temperatures that reduces this effect – the range depends on the SOFC [76]. Finally,

another matter is the heat recovery after cleaning, which is boosted at 750 ºC typically [76].

The basic functioning of the SOFC is now explained [77]:

1) The two input flows enter into the SOFC simultaneously: The biogas passes over the

anode while ambient air passes over the cathode.

2) In this step the CH4 present in the upgraded biogas is brought under a steam

reformation in the anode, producing the reformed fuel (H2).

3) Once this hydrogen crosses the anode, it attracts oxygen ions from the cathode, which

immediately combines with the H2 to produce electricity, heat and carbon dioxide

(which can be captured at the same time that the CO2 present in the biogas mix).

Analysing the individual reactions of the hydrogen in the anode and cathode it can be seen

that, starting with the anode, the chemical reaction is [78]:

2H2 + 2O2- → 2H2O + 4e-

While in the cathode:

O2 + 4e- → 2O2-

Nevertheless, it has not been taken into account that pure hydrogen is not used in the SOFC,

and the hydrogen would come from a steam reforming of the CH4, using the temperature

released by the SOFC operation to do this endothermic reaction – this is really important, since

no external devices are needed to give energy to the cell to do the steam reforming, since it

uses its own energy. Then, in the anode there occur more reactions, that ordered would be

[79]:

(1) Steam reforming reaction: CH4 + H2O → 3H2 + CO

(2) Water-gas shift reaction: CO + H2O → H2 + CO2

• Overall reforming reaction: CH4 + 2H2O → 4H2 + CO2

The idea is that with the CO produced in the steam reforming more hydrogen is obtained in

the water-gas shift reaction. Then, the H2 would follow the electrochemical reactions previously

described for a SOFC that is using just hydrogen as fuel. The idea is that at the end all the

reactions results in the production of electricity, heated air (oxygen is the oxidizer, but N2 is

also present in the reactions even if there is small interaction: if there is any NOx could be


created) and CO2. To avoid dangerous carbon dioxide emissions, the CO2 is typically

sequestrated by the technologies explained later on. Since there are many reactions in the

anode, it seems interesting to visualize the process in an image. Then, Fig. 7.2 a) shows the

SOFC schematic, Fig. 7.2 b) shows its physical model and boundary conditions and finally Fig.

7.2 c) shows the electrochemical and reforming reactions in the anode [79].

Fig. 7.2. a) Schematic of a planar SOFC, b) physical model and boundary conditions and c) reforming

and electrochemical reactions in the anode of the SOFC. (Source: [79]).

Regarding the structure of a SOFC there are two main kinds [80]:

• Planar SOFC: The cell components are structured as flat plates connected in

electrical series, configuring a SOFC in layers.

o Short stack planar (i.e. company Julich)

o Integrated planar (i.e. company Rolls Royce)

• Tubular SOFC: The cell components are configured as thin layers on a cylindrical

tube, the reactions are identical but the need of gas-tight seals is eliminated.

o Large diameter: diameter > 15 mm (i.e. company Siemens Westinghouse)

o Microtubular SOFC: diameter < 5 mm (i.e. company Adelan)

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On this project planar structure is considered, since it is the most extended one. Once this is

clear, the comparison between the advantages and disadvantages of using a SOFC or a gas

cycle is made in further points, but now it can be made the advantages and drawbacks that

brings using CH4 as fuel for the SOFC instead of H2.

Starting with a clear advantage: The H2 is mostly obtained nowadays from grey reforming [70],

called this way since it comes from a fuel (CH4) producing CO2 as a product – steam reforming

is a type of grey reforming. For this reason, using the CH4 directly in the SOFC makes the

overall system’s efficiency higher than first doing the reforming in a separate device and then

using the obtained H2 in the SOFC.

There other ways for obtaining H2 such as the electrolysis in alkaline/ PEM electrolysers (now

new technologies based on reversible SOFC are being developed, to produce H2 with

electricity). Indistinctly, the overall efficiency of first obtaining the H2 in an electrolyser and then

using it in a SOFC would be much lower than using CH4 directly in the SOFC, using the

released heat by the cell heat to make the endothermic reforming reactions of methane.

CH4 is obtained when producing biogas from organic waste, residues and resources,

generating a positive impact in the world since the energy is clean and renewable. On the

same way H2 can be obtained in other processes from unused energy, such as the excess

wind power that is currently curtailed. But obtaining hydrogen from the cattle manure and

biomass won’t be efficient at all.

On the other hand, there is a clear disadvantage: The CO2 production if methane is used. With

hydrogen as a fuel, the only products are hot non pollutant gases and water, while if the fuel is

biogas carbon dioxide would appear as a product of the steam reforming. Thereupon, carbon

sequestration is essential to avoid emissions of polluting GHGs; ensuring a green and

renewable method for producing electricity and heat – later on it would be explained which

Carbon Capture and Storage (CCS) technologies can be used in SOFC.

Finally, a very important constraint of the SOFC is presented, since it would directly affect to

the sizing of any system based on this technology: SOFC are not able of activate themselves

in a quick response, being sensible to fast power variations. In other words, this system is

bound to produce constant power without being capable of adapting to a variable demand

constantly [70]. This is not a minor problem, because even if they can work at partial load the

sizing should be done considering a constant power delivered by the cell.


7.2.2. Sizing and results of alternative 1

At this point, considering the technology described and understood, let’s size the system and

find a specific model of a SOFC with the conversion efficiencies and properties. Actually, the

next consideration has been done an it would be applicable to this alternative and alternative

number 3, both conversion technologies based on a SOFC:

• The EGS is going to be sized to transform all the biogas produced in the co-digestion

process into electricity and heat. This means that for sizing the system the maximum

and minimum hourly demands won’t be a constraint to consider while sizing and

choosing the models of the conversion systems.

Nonetheless, knowing the energetic needs of Can Barrina is essential because with the EGS

selected it would happen that at some specific hours – actually in theory all of them – the

thermal and electrical demands won’t be identical to the thermal energy and electricity

produced by the EGS. Since the hourly demands for all the year have been approximated, it

is possible to find now:

A) Hours that have excess energy: In that case, electricity that is not self-consumed would

be injected to the electric grid and sold. The case of the excess heat is more delicate,

because near Can Barrina there are not buildings or services where this energy can

be used – if the thermal production is higher than the heat demand of the anaerobic

digester and the farm together, this energy won’t be used.

B) Hours that don’t have energy enough to cover the demands: Electricity could be taken

from the grid and, if there is not enough thermal energy, a redesigning of the system

would be done to save some biogas to be burned in an auxiliary boiler. The co-

digestion process cannot be interrupted

Then, the next step is finding a model with the maximum nominal power that can be supplied

along the year with the available biogas. In the project LARGE-SOFC Towards a Large SOFC

Power Plant many SOFC from different manufacturers are compared, from the order of some

kW installations to tens of MW. The model WFC50 from Wärtsilä Findland, which reached

37,5±1,9 % of electrical efficiency at 52 % power level and approximately 42 % of electrical

efficiency at nominal power [81], was chosen. The thermal efficiency would be equal to 47 %

- considering overall efficiency of 89 %. The cost of this technology can be approximated to

1000-2500 €/kWe installed [81], [82]. This specific model works at 750 ºC in continuous

operation giving a high grade of exhaust heat [81], [82].

The total efficiency of the SOFC is calculated as seen in Eq. 7.1; where the electrical power

output is the electricity produced, the heat output is the thermal energy of the exhaust gases

and the heat input is based on the LHV of the CH4 existing in the biogas consumed.

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𝜂𝑡 = 𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑎𝑙 𝑝𝑜𝑤𝑒𝑟 𝑜𝑢𝑡𝑝𝑢𝑡+𝐻𝑒𝑎𝑡 𝑜𝑢𝑡𝑝𝑢𝑡

𝑇𝑜𝑡𝑎𝑙 ℎ𝑒𝑎𝑡 𝑖𝑛𝑝𝑢𝑡 (Eq. 7.1)

Fig. 7.3 shows an image of the a real WFC50 installed in the city of Vaasa, Finland. Its internal

structure can be seen in Fig. 7.4 – where the anode and the cathode are placed in the left side

of the schematic (the other elements are valves, pumps, pipes, refrigeration devices…).

Fig. 7.3. WFC50 SOFC installed in Vaasa in 2008. (Source:[81]).

Fig. 7.4. Internal structure and design of the WFC50kW unit. (Source: [81]).

The prices and nominal powers of the SOFCs are always in electrical base, so it means that if

a specific model is described as a 50 kW SOFC, at nominal conditions 50 kWe are going to be

produced – considering the efficiencies of the model WFC50 the thermal power output would


be then 55,95 kWth. Besides, the electrical efficiency is always base on the LHV of the fuel (H2,

NG, biogas…). Thus, if the WFC50 is supplying 50 kWe, considering its electrical efficiency of

42%, 119 kW of biogas would be consumed at that specific moment – at nominal conditions.

The expected lifetime ascends to 100.000 hours of operation.

From the 84622,42 m3/year of biogas produced only 55913,5 m3/year are CH4. Actually, the

energy balance is done with the methane, since is the only molecule of the biogas that would

produce power in the SOFC. This means that the methane power (from LHV base) would be

equal to 556028,7 kWh/year. In power terms, it can be easily calculated that the maximum

power consumed – in form of biogas – by the SOFC would be 63,47 kW to maintain a constant

production during the year. For this reason, the size of the selected cell would be equal to

26,66 kW (obtained by multiplying the maximum power supplied in form of biogas over the

year per the electrical efficiency of the WFC50). Wärtsilä produces cells from 20 kWe-50 kWe

of the previously mentioned model, so it can be purchased a model of 26,66 kWe – assumed

to have the same properties and efficiencies that the WFC50.

As a matter of a fact, the thermal power can be also known, delivering a power equal to 29,83

kWth. Hence, the annual production – thermal and electrical – for a year with the SOFC working

the 8760 h at nominal power can be appreciated in Fig. 7.5.

Fig. 7.5. Hourly thermal and electrical generation by the selected SOFC if functioning at nominal

power uninterruptedly. (Source: Own).

Now, it is assessed how this generation would meet with the existing demand of Can Barrina

plus the new demand of the anaerobic digester. It can be easily studied since the hourly

0

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Thermal and electrical generation over the year

Thermal generation Electrical generation

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demand is known, and now the hourly production too. Let’s start with the electric part.

A) Electricity balance between generation and production

The 213.118,5 kWhe/year of electricity that are expected to be consumed in Can Barrina –

from which 130.908 kWh corresponds to the existing demand on the farm and 82210,5 kWh

are required by the biogas production system (anaerobic digester and associated devices) –

are less than the 233.532,05 kWhe/year produced by the SOFC. Nonetheless, there is an

important problem and it is the time mismatch between generation and demand. From the

8760 h of the year in 5582 h the electricity produced by the SOFC is enough to cover the

electric needs of the farm and biodigester (from now own just named electric needs of the

farm). However, the in remaining 3178 h the electricity required by the farm during that hours

are larger than the 26,66 kWhe generated by the SOFC hourly. In fact, from the total electrical

demand:

• 27993,63 kWhe/year would not be covered by the proposed EGS with this SOFC. This

means that the 13,135 % of the electrical demand won’t be fully covered by the SOFC.

• The remaining 185.124,92 kWhe are completely covered by the system. This means

that an 86,865 % of the electrical demand could be directly self-consumed – assuming

not power losses in the transportation of electricity from the SOFC to the devices of the

farm. Actually, this supposes a high degree of coverage by the EGS proposes.

• There is an excess energy equal to 48407,13 kWhe, coming from the hours when the

electricity produced by the EGS is higher than the demand at that specific hour.

In the studied EGS, the 27993,63 kWhe not met by the electricity produced by the SOFC should

be purchased from the electric grid. On the other hand, 48407,13 kWhe would be injected to

the grid so the net metering policies (if any) or the direct selling of the energy could help having

benefits from the energy exchanges between the farm and the grid.

However, there is a critical point here and it is that the higher demands occur usually at peak

periods – when the electricity is more expensive – while the major part of the excess energy

occur at night, at valley hours – when electricity is cheaper. The solution to that problem is

commented at the end of this section.

Now, it can also be studied the seasonal difference between the demand’s coverage over the

year. It has been observed that in colder months (when the electrical demand is lower for the

reasons explained at section 4.3.2), the fraction not covered by the EGS is really small if

compared with the fraction of the electric demand not covered in hotter months (specially July


and August). To visualize this difference, Fig. 7.6 shows the electricity coverage for 1st January

while Fig. 7.7 shows the same comparison for 1st July.

The difference between both days can be seen easily, remarking that in 1st January the

demand is met practically in its totality while in 1st July a great fraction is covered, but there are

some hours with a huge lack of production – the higher peak for 1st July appeared at 17:00,

when 24 kWh of the demand are not met by the electricity coming from the EGS.

Fig. 7.6. Electricity generation and demand on 1st January, standard year. (Source: Own).

Fig. 7.7. Electricity generation and demand on 1st July, standard year. (Source: Own).

This tendency of higher excess electricity rates in winter and smaller coverage fraction in

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Wh

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t (h)

Electricity matching for 1st January

El. demand

El. production

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Electricity matching for 1st July

El. demand

El. production

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summer is expected to change in when analysing the thermal energy demand, since in winter

this demand is higher and in summer smaller (contrary to what happens with electricity).

B) Thermal energy balance between generation and production

On the other hand, the annual thermal demand ascends to 101.509,35 kWhth/year summing

the farm’s current demand (17704,27kWhth/year) plus the anaerobic digester’s thermal

demand (83805,08 kWhth/year). Actually, the thermal energy produced by the proposed EGS

would be equal to 261.333,49 kWhth/year; actually, more than the double than the thermal

needs. Obviously, here some thermal losses must be considered in the transport of heat and

in the heat exchanges to adapt the hot exhaust gases of the SOFC into usable energy in the

biodigester and the pig farrowing house. Nonetheless, even considering a very pessimistic

transport and heat exchange efficiencies of a 70% the thermal demand is fully covered for all

the hours of the year.

In fact, using only the half of the thermal energy provided by the SOFC 8411 hours of the year

would be fully covered by the energy generated in the EGS. In other words, there is a

tremendous excess of thermal energy – in point of fact 159.824 kWhth/year won’t be used.

There is no graphic here that hides the clear problem of this EGS, and it is a tremendous waste

of energy in form of heat. This energy cannot be stored in technology at a reasonable cost,

and what’s more important, even if it is stored it neither can be transported efficiently nor used

in the farm.

For this reason, the Alternative 3 is expected to solve this problem by adding a GT at the exit

of the SOFC to take profit of the thermal energy, loosing part of it in the conversion but

producing more electricity. This would lead to a scenario were the overall efficiency of the EGS

would be much lower but the fraction of energy self-consumed would be much higher, because

it can be ensured supplying all the thermal demand incrementing at the same time the electrical

fraction covered.

In other words, the idea is to ensure the thermal energy coverage, but increasing the electric

one with the GT. What’s more important, if we have to choose between having excess

electricity or excess heat, the best choice is clearly having extra electricity: As it can be injected

and sold to the electrical grid.

7.2.3. CO2 sequestration

Regarding the CO2 sequestration, it is important to design a system to avoid unnecessary and

dangerous emissions of this gas. Fortunately, the CO2 stream produced in the normal


operation of a SOFC (plus the part of carbon dioxide present in the biogas) is pure and easily

separable from other molecules. Then, capturing or sequestering this pollutant becomes easier

than in power plants where this gas is mixed with many others. The objective becomes then

finding which of the plausible CCS systems suits better with the EGS assessed. The options

considered were:

• Geological storage: In this method carbon dioxide is injected directly underground,

generally in supercritical form in oil and gas fields, saline and saline-filled basalt

formations and coal mines with difficult coal extraction [83]. Countries like UK, Norway

and Nederland are leading this CCS technologies and projects.

• Direct CO2 storage: The carbon dioxide is derived to a specific storage tank where it

can be stored. The main problem is what is done once the tank is full and needs to be

replaced by another one.

• CO2 compensation: This alternative is not a CCS, but is a wide-spread way of avoiding

the carbon taxes in large industries, and it consist in introducing to the public gas grid

some biogas. In that way, the CO2 coming from the SOFC would be emitted, but the

amount of biogas added should compensate those CO2 emissions. Companies like

Toyota are promoting this actuation to “decarbonize” their industries. This method

won’t be used since all the biogas is expected to be used.

The trouble in this EGS is not separating the CO2 from the biogas since the SOFC already

does this separation (so neither membranes or the CO2 separation methods assessed in

section 6.2.2 are useful now). The only problem is what can be done with the carbon dioxide

once is captured. Fig. 7.8 shows various actions to avoid CO2 emission.

Fig. 7.8. Storage of CO2 in various forms; geological storage, pond with bacteria, transportation with

pipelines and usage in carbon-based industry. (Source: [83]).

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I reckon that this choice cannot be made by me, objectively. The client could decide to pay an

injection system to make geological storage, emit the CO2 and compensate it, use storage

tanks which could be sold and transported to give a use for this CO2 (like in refrigeration

cycles…) or finally, the worst option environmentally talking, emitting this CO2 lowering down

the carbon savings of the EGS. To make the economic and environmental analysis it is

assumed a cost for CO2 storage and that the totality of it is captured and stored, but a CCS is

not chosen. This is assumed also for the EGS based on the conversion alternatives 2 and 3.

7.3. Alternative 2: Gas cycle

7.3.1. Description of gas cycle

A convectional Brayton cycle is proposed in this assessed alternative. Just as a remembering,

this cycle has the following basic steps:

1. Compression: Ambient air is compressed using a compressor, which uses the energy

generated by the rotational movement of the turbine to compress air.

2. Combustion: The fuel, in this case 99 % CH4 (or biomethane), is mixed with the air in

the combustion chamber and it is burned/combusted to heat up the compressed air

incrementing a lot its enthalpy.

3. Expansion in the turbine: There is an expansion of the air inside the turbine, reducing

a lot its pressure but transforming its enthalpic energy into mechanical energy

(rotational movement) of the turbine, which has an axis connected to a generator to

produce electricity.

Then, the basic points of the described cycle would be the four that can be appreciated in Fig.

7.9, being point 1 the ambient air at atmospheric pressure, point 2 this same air compressed,

point 3 the air after passing thought the combustor and finally point 4 the exhaust gases (which

are still at high temperature). In fact, to increment the electrical efficiency usually a regenerator

is used, putting a heat exchanger between point 2 and 3 of the described cycle and the exhaust

gases. The idea is to use the high temperature of the exhaust gases to pre-heat the air before

it enters to the combustion chamber, so higher enthalpy can be achieved at the exit of it –

meaning higher electrical efficiency, but loosing thermal one. This system with only one turbine

is the expected one for a small system. There are some diesel, gasoline and gas “gen-set”

units that allows the instantaneous production of electricity at low power capacities.


Fig. 7.9. Schematic of a basic Brayton gas cycle, Pressure-Volume (P-V) diagram and Temperature-

Entropy (T-S) diagram, respectively. (Source: [84]).

In large CHP plants there are usually two turbines: The high pressure and the low pressure

one. In that cycle there is high pressure between the exit of the compressor and the entrance

to the high-pressure turbine, then an intermediate pressure between the exit of the first turbine

and the entrance of the second, and finally a low pressure at the exit of the low-pressure

turbine. Between both turbines the air at intermediate pressure enters again in the combustion

chamber, to increment again its enthalpy and extract more energy in the second turbine.

Despite the fact that using two turbines tends to boost the total efficiency, its not used

commonly in such small systems as the designed one (higher costs, harder installation…).

In Fig. 7.10 it can be seen the expected disposition for an EGS similar to the expected one for

Can Barrina and a gas cycle as conversion technology.

Fig. 7.10. Schematic design of a standard CHP biogas-based plant. (Source: [84]).

Pág. 128 Report

Fig. 7.10 describes a co-digestion process of biomass and pit to produce biogas, upgraded in

the gasometer and used in the gas engine group to produce electricity and use the heat by

making a heat exchange between the exhaust gases and the “cold” water/air used in the farm

(typically water). In next section a specific model of a GT, the sizing and the fraction of the

electrical demand covered by the EGS would be assessed.


Once the gas cycle basics are clear, let’s size the conversion technology for this alternative. A

crucial consideration must be remarked that makes this system very different with respect the

SOFC: the possibility of changing rapidly the power delivered. In other words, the technology

allows changing rapidly the electrical power output adapting the generation to the real

instantaneous demand. It is assumed that the GT can follow the demand perfectly (even if this

is not true in reality).

Then, the constant power output can now be changed by a variable one, affecting directly to

the sizing criteria. In the case of the SOFC, it was interesting to size the system to the nominal

power that ensures a constant production with the use of all the biogas generated in the

biodigester. That has the problem, as it was mentioned before, that in some hours there is the

necessity of taking electricity from the grid to cover the demand. However, in this alternative

the gas cycle would be sized with the maximum power criteria. In other words:

• The GT should be sized to have, at least, enough electrical power capacity to cover

the energy needs of the hour – of the standard year – with maximum demand. From

Fig. 4.29 it was extracted, and now is remembered, that the maximum demand in Can

Barrina occurred the 1st August from 17:00 to 18:00, with a total hourly consumption of

46 kWh. Nonetheless, now it must be summed the electrical consumption associated

the biodigester; resulting in a maximum demand of 55,85 kWh the 5th August from

17:00 to 18:00. In that case, the day of maximum demand has changed taking into

account the electric load associated to the biodigester, being this demand for the 1st

August at same hour equal to 55,35 kWh (almost equal, but lower). It is logical to have

peeks at 17:00 since is when the 2nd milk extraction turn ends and water is heated up

to 60 ºC to clean the facilities (remember section 4.3.2).

Thereupon, considering constant production during each hour (because approximating the

demand each second resulted impossible), the GT must be able to generate at least a power

output equal to 55,65 kWe. Then, another important consideration must be done, and it is the

minimum power that the GT can supply. In this case, the minimum demand is found the 15th


July from 5:00 to 6:00, being equal to 11,2 kWh. If the GT can supply this energy working at

partial load, there wouldn’t be any problem; otherwise, extra energy would be injected to the

electrical grid. The next step is finding the efficiency and characteristics of a real GT, and see

how generation can meet with demand.

Actually, for such small applications only Micro-gas turbines (Micro-GTs) can be used, being

ranged from 30 kW to over 200 kW [85] (or 30 kw to 500 kW according to [86]). Unfortunately,

the scaling down of the technology results in negative impact in the “heat and combustion

processes” reducing the turbine electrical efficiency, according to [85]. Usually the electrical

efficiencies of Micro-GTs are ranged from 15% to 30 % [85]–[87]. Table 7.2 shows a

comparison between most used NG-based systems.

Table 7.2. Type and properties of heat engines used in packaged CHP for buildings. (Source: [85])

In fact, the reason why a Micro-GT was preferred instead of an internal combustion engine is

because at low power capacities they can offer a similar electrical efficiency (if a heat

recuperator is fitted in the exhaust hot gasses to “pre-heat compressed combustion air to

reduce fuel consumption and achieve efficiencies up to 30 % [85]) having an overall efficiency

around 80 % for the CHP installation – higher than the one of an internal combustion engine

at ow power ranges [85], [87]. Without the recuperator the overall efficiency goes typically

around 70%-75 % [85]–[87].

Nowadays, the company Capstone Turbine has a 51,4 % of the global market share in

microturbines, flowed by Blandon Jets with 19,4 %, MTT with 13,6% and other companies with

smaller impacts [88]. Then, the commercialized 60 kW Capstone Turbine named ModelC60

offers the best performance between the analysed Micro-GTs (it includes the turbine,

combustion chamber and compressor, and so the calculations of electrical and thermal

efficiency). Its electrical efficiency (based on LHV of CH4) is equal to 28±2 %, its thermal

efficiency reaches a 47 % (with an overall efficiency of 75 %) and the exhaust gas temperature

would be around 305 ºC [89] – all at ISO conditions and working at nominal power. In fact, the

affectation of the ambient temperature in the electrical net efficiency developed by the

ModelC60 is shown in Fig. 7.11.

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Fig. 7.11. Nominal rating net efficiency vs ambient temperature for the ModelC60. (Source: [89]).

The next really important parameter to consider is the affectation of the degree of power used

if compared with the nominal one to the electrical efficiency. In other words, the efficiency of

the Micro-GT would change between an operation at nominal power and an operation at partial

load. It has been found that power outputs larger smaller than 10 kW the electrical efficiencies

plummet. In fact, the efficiency in function of the power capacity at which the Micro-GT is

working is showed in Fig. 7.12 from 0 to 25 kW delivered, after this the efficiency is assumed

to be the same that the one at nominal conditions from 25 kW to 60 kW.

Fig. 7.12. Micro-gas turbine efficiency at partial loads. (Source: [90]).


The idea is that at full load the efficiency can reach 28 %, and at east is known that from 9 kW

to 60 kW the electrical efficiency would be at least a 20 %. Fortunately, the was calculated

previously and it is equal to 11,2 kWh from 5:00 to 6:00 of the 15th July (and then all that hour

the Micr-GT is expected to work at 11,2 kW, with an efficiency of 22 % extracted from Fig.

7.12).

Knowing this, the hourly biogas consumption needed to cover all the demand until the biogas

is finished can be known. The idea is that with the low electrical efficiency of Micro-GT all the

annual demand would not be covered, but at least is can be calculated the fraction of the total

electrical demand covered by this EGS. To visualize the results, results are displayed as a list

of days with fully coverage and those where the biogas would have already ended. In reality,

this wouldn’t happen like this because biogas is produced constantly over the year. The taken

solution is presented later on. Regarding the CO2 emissions, in this alternative they would be

released into the atmosphere.

A) Electricity balance between generation and production

In a system such as the proposed one the only problem that may happen is that we run out of

gas. The way of seeing if this can happen passes by comparing the total hourly demand with

the total energy that can be produced with the EGS.

In this alternative the calculations differ a lot from the ones done in the case of the SOFC.

Actually, the objective is in this case finding how much biogas would be consumed each day

and when the 55913,5 m3/year of CH4 at our disposal (99% pure after passing thought the

GCU for this alternative, as mentioned in previous sections) would end if all the demand is

covered. It has been made the assumption that we won’t run out of biogas, and then it would

be decided how the available amount should be distributed over the year. An important factor

to consider while choosing this distribution is that at lower demand rates the efficiency of the

whole gas cycle is worst (remember Fig. 7.12). In fact, in Table 7.3 it is approximated the Micro-

GT efficiency depending on the partial load fraction (it is started from 11 kW since it is the

minimum demand).

Power Output (kW) Efficiency (%) Power Output (kW) Efficiency (%)

11 22 18 24,7

12 22,8 19 25

13 23,5 20 25,5

14 23,9 21 25,7

15 24,1 22 26

16 24,3 23 27

17 24,5 24-60 28

Table 7.3. Approximated efficiencies at various power outputs for the Micro-GT. (Source: [90]).

Pág. 132 Report

Now, the calculations of the required biogas consumption each hour of the year are carried

out, by dividing the electrical demand per the expected efficiency of the Micro-GT at that

electrical power output. It has been assumed that over 24 kW the efficiency of the turbine is

the same that at full load (28 %). Besides, the effect of the ambient temperature is neglected,

since the system would be in an inner building – with an assumed mean temperature of 16 ºC

– and the efficiency drop is not clearly manifested until the ambient temperature exceeds 21,26

ºC (70 F, see Fig. 7.11).

The results are an annual CH4 consumption equal to 800.448,88 kWh/year (based on LHV)

for supplying all the electrical demand with that EGS. Table 7.4 shows the amount of

consumed energy – in form of biogas – at the end of the year for each power interval. With

that consumption the electric needs of the farm could be covered from 1st January to 13th

September (to be more precise until 13:00, being 5845 hours covered by the EGS.

Nonetheless, this is not the best way of distributing the consumptions for the reasons exposed

later on.

Required CH4 consumption at each power interval for supplying all the electrical demand

Power Output (kW) Biogas cons. (kWh) Power Output (kW) Biogas cons. (kWh)

11-12 52090,45 18-19 26804,32

12-13 475,76 19-20 36219,70

13-14 37582,75 20-21 32396,49

14-15 3728,88 21-22 47688,37

15-16 0 22-23 0

16-17 23768,07 23-24 0

17-18 35873,11 24-60 503.820,98

Table 7.4. Energy consumed at each electrical power output interval to meet the whole annual

demand. (Source: Own).

From Table 7.4 it can be concluded that the vast majority of the demand is covered by the

Micro-GT working at its higher efficiency (obtained over 24 kW of electrical power output). That

is to say, 503.820,98 kWh/year of upgraded biogas would be consumed for the hours with

electrical demand higher than 24 kWh. In other words, 50663,56 m3/year of CH4 from the

available 55913,5 m3/year would be consumed when the Micro-Turbine efficiency is maximum.

The best way of distributing the biogas consumption would be the following:

• Prioritize the biogas consumption for the hours when the electrical demand leads to

higher Micro-GT efficiencies. In this way less amount of biogas would be required to

cover the same demand.


Then, if it was said than 50633 m3/year of biomethane are needed for covering the demand at

higher required power outputs, this demand should be covered since it can be met by the EGS

working at its maximum efficiency. Then, the remaining 5249,94 m3/year should be distributed

prioritizing the higher electrical demands. Actually, the demand covered with power outputs

from 21-22 kW would require 4795,48 m3/year which can be supplied, but the demand covered

by the Micro-GT working at 20-21 kW cannot be fully covered (only 454,46 m3/year out of the

required 3257,75 m3/year).

Then, supposing that there is a storage system that allows a selectivity in biogas usage;

152.907,89 kWhe/year could be covered, meaning a self-consumed fraction of the 71,75 %.

The rest of the electricity demanded (60210,66 kWhe/year) should be purchased from the

electrical grid. If the biogas distribution had been scheduled to give a constant power

production, this self-consumed fraction would have diminished a lot.

B) Thermal energy balance between generation and production

Nonetheless, distributing the electrical production is the previously explained way would have

a tremendous drawback that affects directly the thermal energy balance between generation

and demand, and it is a lack of energy in all the hours with hourly demand smaller than 21

kWh (because electricity would be taken from the grid and thermal energy won’t be produced).

Actually, the thermal production is larger in this EGS than in the previous one with the SOFC,

but on contrary than the previous case now there is larger thermal productions concentrated

in less hours of the year.

Actually, this suppose a tremendous problem because the biodigester needs a constant heat

input the ensure the constant production of biogas and the preservation of the microorganism

in charge of the co-digestion of cattle manure and biomass. Besides, storing thermal energy

would be a utopia – technically and economically – for the scale of the installation. Therefore,

all the previous method for minimizing the biomass consumption (incrementing the overall

efficiency and so on) cannot be used, because it would affect to the biodigester. Consequently,

a new study must be made considering that the biogas generated is directly used in the Micro-

GT. In this case, the constant 63,47 kW of biogas produced could be transformed into 15,3

kWe and 29,8 kWth supplied constantly over the year.

The thermal performance would be then identical (same thermal efficiency) to the one for

expected the SOFC but in comparison the electrical one would be much poorer – 15,3 kWe vs

26,66 kWe. Nevertheless, if this system is used this is the only option. Besides, the Micro-GT

model could be then the ModelC20 of Capstone Turbine instead of the ModelC60. The

electrical efficiencies at 15,3 kWe can be estimated to be the same (from [89]).

C) New electrical energy balance

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Therefore, the electrical generation would be studied as a constant production of 15,3 kWe

by the system. Then, automatically 1812 h (20 % of the year) would be fully covered by

the energy produced by the Micro-GT. For the rest of the year only a fraction is covered.

In general terms, 213.118,55 kWhe/year expected to be demanded in the standard year

the system only would produce 134.002,92 kWhe/year. From this energy generated 6426

kWhe/year will be injected to the grid because they are excess energy in the hours when

they are produced. The energy that would be required to be taken from the grid is equal to

85542,53 kWhe/year.

Actually, some biogas could be saved to take profit of the 6426 kWhe/year that are “thrown

energy”, but this only suppose a 4,78 % of the energy generated during the year by the

Micro-GT and would imply higher investments in storage technologies and biogas control

valves and actuators: For this reason, it is maintained the idea of a constant production

also for this alternative in the conversion technology. Fig. 7.13 is comparing the electric

coverages for this alternative and the previous one (with the SOFC) for the 1st January,

and Fig. 7.14 is doing the same for 1st July. In this way, it can be seen the difference

between both alternatives.

Fig. 7.13. Electrical demand and comparison between production for alternative 1 and 2 for the 1st

January of standard year. (Source: Own).

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El. demand El. Production SOFC El. Prodruction Micro-GT



July of standard year. (Source: Own).

To sum up, the sizing of the EGS based on a Micro-GT as the conversion technology has been

firstly studied to maximize the electrical production and the overall electrical efficiency of the

system. Unfortunately, the biogas distribution taken to do this optimization was incompatible

with the thermal demand, so another strategy that ensures covering the thermal demand too

had been taken (specially because the anaerobic digester needs constant supply to maintain

the biogas production) – besides, only looking for improving the electrical efficiency would need

the purchasing of new thermal generators jeopardizing the economic profitability. The results

have been obtained for a constant biogas consumption for the reasons previously mentioned.

7.4. Alternative 3: SOFC combined with a gas turbine

7.4.1. Description of SOFC with Micro-GT

The last conversion technology studied is a combination of the two previous alternatives (1

and 2); meaning a SOFC with a Micro-GT that uses the hot exhaust gases to produce more

electricity. The main idea is to use the maximum thermal energy as possible to increase the

electrical efficiency, since in the previous EGSs it was found out that the excess thermal energy

would be tremendous while there is a lack of electricity when producing constant power.

This doesn’t mean that the coverage of the thermal demand is not essential, in fact, in case

that some of the critical thermal loads couldn’t be covered at constant biogas consumption

(needed by the SOFC) the turbined exhaust gases would be reduced – decreasing the

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El. demand El. Production SOFC El. Production Micro-GT

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electricity generation but ensuring the coverage of thermal demand. Nevertheless, before

considering any strategy alternative to a constant electrical and thermal power generation the

study the first study is done (because it can be maximized the production for a specific nominal

power of the SOFC).

Many articles remarks the clear improvement in the electrical yield by implementing the Micro-

GT [68], [69], [73], [81], [91]. Regarding the composition of a SOFC-Micro-GT (SOFC-MGT)

system, the article Integration of a municipal solid wate gasification plant with solid oxide fuel

cell and gas turbine ([69]); shows the typical one for this kind of system having a gasifier in

charge of transforming the municipal solid wastes into syngas (instead of an anaerobic digester

producing biogas), as displayed in Fig. 7.15 – where a) shows that system with the basic

components and b) the same system with an hybrid recuperator to pre-heat the compressed

air before entering into the combustion chamber (increasing the electrical efficiency for the

reasons explained in gas cycle study).

Fig. 7.15. Scheme of gasifier and SOFC-MGT plant: a) without recuperator b) with hybrid recuperator.

(Source: [69]).

Clearly, the individual functioning of both technologies – SOFC and Micro-GT – is no longer

needed to be explained again. Besides, all the internal points of the cycle were not calculated

as they had not been calculated before for the previous alternatives. This is because in this

project it is being sought for the optimal technology technically and economically, but the

individual sizing of all the internal components of a SOFC or a gas cycle is considered out of

the scope of this project. The main idea is comparing the technologies in costs and optimal

coverage of the demand: And this can be done by studying the efficiencies for already existing

devices that can be purchased, without entering in detail on all the internal components


existing in that technologies. Obviously, by designing all the points of the gas cycle or of a

SOFC all the transformations and energy balance could be done to obtain more accurate

results of the final efficiencies and the intermediate points of the cycle for the most suitable

system for Can Barrina; but in has been opted for relying in the efficiencies and parameters

given by manufactures or already existing installations. For example, Fig. 7.16 shows the basic

composition of the SOFC-MGT part of the Viking gasifier plant situated at the Technical

University of Denmark, where they succeed in incrementing the electrical efficiency of a SOFC

with 𝝶e_SOFC = 36,4 % and a Micro-GT with 𝝶e_Micro-GT = 28,1 % up to 𝝶e_SOFC-MGT = 50,3 % by

combining these technologies [91].

Fig. 7.16. Flow sheet of the SOFC-MGT of the article [91]. (Source: [91]).

Another parameter that is now briefly studied theoretically is the pressure ratio and how it

affects to the overall efficiency of the system. As it has been mentioned in previous sections,

the increment of pressure can affect positively to the singular efficiency of the SOFC [71].

Besides, in a hybrid system it is essential to compress air at a specific Pressure Ratio (PR) to

obtain optimal efficiencies at the Micro-GT. This happens because for compressing the air at

higher pressures more energy is consumed by the compressor, but if this air is not enough

compressed the gas expansion inside the Micro-GT won’t generate enough energy: and

actually, there is a specific PR that maximized the overall efficiency. For this reason, the

affectation of the PR in the gas cycle of the Viking gasifier plant – mentioned in the previous

paragraph – is displayed in Fig. 7.17 for the SOFC working at 1 atm and with an internal

temperature of 800 ºC (actually they studied also the affectation of increasing the internal

temperature of the cell in the electrical efficiency performed).

Pág. 138 Report

Fig. 7.17. Energetic electric efficiency at different operation PRs over the air compressor of the Viking

gasifier plant at Technical University of Denmark. (Source: [91]).

Actually, with the experiments carried out using the Viking plant they found out a very

interesting issue, and it is that the optimal PR of a gasifier plant using a Micro-GT is not the

same than the one for the same plant but using a SOFC-MGT as conversion technology. In

fact, for the case of the Gasifier-Micro-GT plant the optimal PR was 3,7, while for the Gasifier-

SOFC-MGT configuration it was lowered down to 2,5 (and for the Gasifier-SOFC it was 1,

since exhaust gases won’t be used to produce electricity). Fig. 7.17 also shows this

comparison depending on the plant’s configuration and PR. Thereupon, this ratio is assumed

to be the optimal one also in the SOFC-MGT group of this alternative, since it is not specified

in the data found for the pre-design plant used in next section.

In next section the sizing and the results of the calculations performed to assess the electrical

and thermal coverage of the demands using this conversion technology are shown and

explained as has been done for the previous alternatives.


As it was explained in section 7.2.2, the sizing of the conversion system is based on taking

profit of all the biogas produced in the EGS, resulting in a constant power and thermal

generation over the year. The power consumption would be the biogas generated and this

does not differ from alternatives 1 and 2 (63,74 kW). The resulting electrical and thermal power

outputs would depend on the system’s efficiencies – considering that in this alternative there


are changes only in the usage of the exhaust hot gases of the SOFC, all the considerations

made in alternative 1 to find the optimal size for the SOFC are maintained now.

Once this was clear, it was looked for the existing system that performs better electrical

efficiencies (since the thermal production can be boosted easily by transforming less energy

of the exhaust gases of the SOFC into electricity). The electrical efficiencies are expected to

be larger than 50 % by combining both technologies in the described hybrid cycle [69], [73]. In

fact, for this alternative the SOFC-MGT system of Rolls-Royce Fuel Cell System (RRFCS) are

assessed (they fabricate hybrid systems from 15 kWe up to large systems of some

megawattse). In the project LARGE-SOFC: Towards a Large SOFC Power Plant ([81]), it is

presented an already existing RRFCS hybrid plant of 266 kWe with an electrical efficiency of

55,2 % (see Fig. 7.18). For this size of the plant, it has been found that with a cathode blower

instead of an ejector and improving the Micro-GT the efficiency can go up to 59,8 % using the

same SOFC. The lifetime of the system would be equal to 15 years with the SOFC working

8000 h/year [81], this means 13,7 years working uninterruptedly – and so would be considered

in the economic analysis.

Fig. 7.18. Current RRFCS Hybrid Plant of 266 kWe. (Source: [81]).

Coming back to the size expected for our EGS, it is important to mention that this high electrical

efficiency of almost 60 % would never be achieved in a smaller system, because at it was

mentioned while analysing the Micro-GTs, at higher sizes of the turbines higher electrical

efficiencies can be obtained. In fact, by combining the model WFC50 from Wärtsilä Findland

– with electrical and thermal efficiencies 42 % and 47 % respectively – and the ModelC20 of

Capstone Turbine – with electrical efficiency of 24,1 % and thermal one of 47 % working at

15,3 kWe – an overall electrical efficiency of 54,77 % could be obtained by taking profit of all

the thermal energy going out of the SOFC. For that combination, and neglecting any kind of

losses, the total thermal efficiency would be 22,09 % (obtained by multiplying both thermal

Pág. 140 Report

efficiencies, since it would be the thermal energy at the exit of the Micro-GT).

At the end, a smaller RRFCS with a cathode blower instead of an ejector is assumed to have

an electrical efficiency of 55 % and a thermal one of 22 % (total efficiency of 77 %): Meaning

that with the constant input of biogas of 63,47 kW it would produce 34,91 kWe and 13,96 kWth.

Fig. 7.19 compares the electrical and thermal efficiency of this alternative with alternative 1. It

can be seen clearly how the amount of usable energy would be higher for just the SOFC than

for the hybrid system, but since there was a tremendous excess of heat alternative 3 adapts

much better to Can Barrina’s necessities boosting electrical production.

Fig. 7.19. Hourly thermal and electrical generation for alternatives 1 (SOFC) and 3 (SOFC-MGT) if

working uninterruptedly all the year. (Source:Own).

Since it may happen that with that constant production the thermal coverage is insufficient, in

this case it is analysed the energy balance between thermal generation and demand first, to

apply any changes later in the electrical generation if necessary. What its clear is that, at least,

the thermal demand of the biodigester must be ensured by the energy generated by the EGS

to avoid buying an auxiliary boiler. Then, it can be evaluated if it would be better using the

existing thermal installation of Can Barrina to match with the unmatched demand (maintaining

the highest possible electricity production) or, on the other hand, derive some heat to the

unmatched loads reducing the electricity production.

A) Thermal energy balance between generation and production

The thermal and electrical demand of Can Barrina and the anaerobic digester would be the

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Thermal and electrical generation over the year for alternative 1 and 3

Thermal generation SOFC Electrical generation SOFC

Electrical Generation SOFC-MGT Thermal Generation SOFC-MGT


same for this case than for the previous alternatives – 101.509,35 kWhth/year and 213.118,56

kWhe/year respectively. In the case of the heat production, there is a significant decrease in

the total thermal power generated with the hybrid system SOFC-MGT; having an annual

production equal to 122.326,31 kWhth/year. Even if the total thermal generation at the end of

the year is higher than the demand, there is a mismatch between the generation and the

production having:

• 21699,62 kWhth/year of excess energy.

• 882,66 kWhth/year not covered by the EGS – actually, it represents only a 0,88 % of

the total demand.

In number of hours covered, it has been seen that with a constant thermal production of 13,96

kWth by the EGS the demand of 7540 hours/year would be fully met by the production (86 %

of the year). On the other hand, the remaning 1220 hours (14 %) won’t be fully covered, but

considering that the maximum thermal demand is equal to 16,77 kWhth from 7:00 to 8:00 am

the 15th February, even for the worst hour the self-consumed fraction is larger than 83 %. For

this reason, almost all the thermal demand would be covered by the system working at

constant power generation rates.

Now, it must be decided if those 882,66 kWhth not covered by the EGS and distributed on the

coldest months of the year should be derived from the EGS or, on the other hand, produced

with the currently used diesel boilers of Can Barrina. The answer to that question is simpler as

it may seem, and it would rely on which option is more feasible technically and economically.

First of all, the maximum thermal demand associated to the biodigester is equal to 10,42 kWhth,

smaller than the 13,96 kWhth produced by the EGS hourly if working at constant generation

mode. Then, all the demand of the anaerobic digester is covered and its operation would never

be put in danger.

The electricity price in Spain can be estimated to be 0,156€/kWhe [92], while the diesel/gasoil

for heating in a boiler 0,1€/kWhth (taking into account a 90% efficiency in the boiler) [93].

Producing an extra 882,66 kWhth would mean purchasing an extra 2206,65 kWhe (electrical

efficiency is much higher than thermal one, so it makes sense that producing extra thermal

energy implies larger electrical mismatches). Therefore, from the economic point of view it is

obviously better produce the thermal energy not covered by the EGS with the diesel boiler

currently used by the farm. Moreover, from the technical point of view it is a superior option

too; because it seems easier to control a diesel boiler (that would work as auxiliary unit) than

all the cycle and fluxes of the exhaust gases released by the SOFC.

In next section the electricity coverage – considering constant thermal and electrical generation

by the EGS with the SOFC-MGT as conversion technology – is studied.

Pág. 142 Report

B) Electricity balance between generation and production

Finally, the expected electricity production for the described EGS for this alternative would

ascend to 305.815,79 kWhe/year – a 43,49 % higher than the electrical demand. Nonetheless,

due to the variable demand there would be the following mismatch:

• 102.130,02 kWhe/year of excess energy.

• 9432,8 kWhe/year not covered by the EGS – representing a 4,43 % of the demand.

Actually, the 95,57 % of the electrical demand should be covered by this system, whereas

using only the SOFC without the Micro-GT system it was covered an 86,87 % approximately

– in next section a deeper comparison is carried out between all the alternatives. Expressing

this electricity coverage in hour basis; the demand would be fully self-consumed by the power

produced by the EGS in 7341 hours and for the remaining 1419 hours it would be partly

covered by the EGS and the rest adjusted by electricity purchased form the electric grid.

The same demand coverage for 1st January and 1st July showed for alternatives 1 and 2 as

conversion technologies (in Fig. 7.7, Fig. 7.8, Fig. 7.13 and Fig. 7.14) is shown now for this

alternative in Fig. 7.20 and Fig. 7.21. It can be clearly seen that for the 1st January there is

much excess electricity during all the day, while for the 1st July in some hours the 34,91 kWe

generated by the SOFC-MGT system are not enough to cover all the electrical demand – but

it supposes a great improvement with respect only the SOFC.


January of standard year. (Source: Own).

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

E (k

Wh

)

t (h)


El. demand El. Production SOFC El. Prodruction SOFC-MGT



July of standard year. (Source: Own).

7.5. Technical comparison between the alternatives

The last part of this section is a final comparison between the three alternatives studied as

possible conversion technologies for transforming the biogas generated into electricity and

heat. In this way, the technical comparison can be visualized easily – using tables. Therefore,

the results obtained in sections 7.2, 7.3 and 7.4 are displayed in Table 7.5 and Table 7.6. On

the one hand, Table 7.5 shows the electricity and thermal production – and the total one by

summing both of them – generated by each of the studied alternatives; considering a constant

production for all the year. It can be appreciated that alternative 1 is the one offering higher

overall efficiency and therefore total energy production. However, this doesn’t mean that the

SOFC alone is the best choice, because the key is how this energy generated meets with the

real demand.

Alternative Elec. Prod. (kWh/y) Thermal Prod. (kWh/y) Total Prod.(kWh/y) 𝝶overall (%)

1. SOFC 233.532,05 261.333,49 494.865,54 89

2. Micro-GT 134.002,92 261.333,49 395.336,41 71

3. SOFC-MGT 305.815,79 122.326,31 428.142,10 77

Table 7.5. Annual electricity, thermal and total production and overall efficiency for each alternative in

standard year at constant operation. (Source: Own).

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

E (k

Wh

)

t (h)


El. demand El. Production SOFC El. Production SOFC-MGT

Pág. 144 Report

On the other hand, Table 7.6 shows the electricity and thermal excess and missing energy at

the end of the year for each alternative, and the percentages of self-consumption. It can be

appreciated how, indeed, alternative 3 offers the best results since is the one that offers a

higher fraction self-consumption – or total coverage – fraction of the demand. The idea is that

more demand would be covered using this technology and less energy would be thrown away.

In this way, the SOFC-MGT arises as the most suitable conversion technology considering the

energetic needs of Can Barrina, plus those that would be associated to the implementation of

the anaerobic digester.

Alternative Excess el.

(kWh/y) Miss. el. (kWh/y)

El. Cov. (%)

Excess heat (kWh/y)

Miss.heat (kWh/y)

Therm.cov. (%)

Total cov. (%)

1. SOFC 48407,13 27993,63 86,86 159.824,14 0,00 100,00 91,10

2. Micro-GT 6426,89 85542,53 59,86 159.824,14 0,00 100,00 72,81

3. SOFC-MGT 102.130,02 9432,79 95,57 21699,62 882,66 99,13 96,72

Table 7.6. Excess and missing electricity and heat, electric and thermal coverage and total demand’s

fraction self-consumed for all the studied alternatives in a standard year. (Source: Own).

Moreover, another tremendous advantage – highlighted in the economic analysis too – is that

alternative 3 leads to a scenario with few excess heat but high excess electricity: This is really

advantageous because electricity could be injected in the electric grid and sold, whereas

excess thermal energy cannot be used easily (no more thermal demand nearby the farm, and

tremendous losses if transported to far-located loads).

Nonetheless, Table 7.6 calculates the percentage covered of the total electrical and thermal

demand including also the biodigester needs. Actually, it interests us the fraction if the current

Can Barrina’s demand that can be covered. It has been supposed that first, all the demand of

the anaerobic digester is covered, and then the system starts supplying energy to meet with

the 130.908 kWhe/year of electrical demand and the 17704,27kWhth/year of thermal demand.

Table 7.7 shows the results for each alternative, giving the real energy savings obtained by

each conversion technology.

Alternative El. Cov. (kWh) El. Demand

Cov (%) Heat Cov.

(kWh) Therm. Demand

Cov. (%)

1. SOFC 102.914,37 78,62 17704,27 100,00

2. Micro-GT 45365,47 34,65 17704,27 100,00

3. SOFC-MGT 121.475,21 92,79 16821,61 95,01

Table 7.7. Electricity and thermal Can Barrina’s current demand coverages (quantity and percentage)

by the different alternatives as conversion technology for the EGS. (Source: Own).


To sum up, in the economic analysis it is studied the best alternative in terms of costs, but in

terms of performance and adaptability to the energy needs of Can Barrina alternative 3 would

be, clearly, the best option.

Pág. 146 Report

8. Economic analysis

In this section the economic analysis of the proposed EGSs (including one for each of the three

conversion technologies studied in the previous section) is carried out. The main idea, is firstly

see which of the conversion technologies offers a better economic performance for a standard

economic study for 20 years away from today. From now on, the three different EGSs are

called as follows:

• EGS 1: Composed by the SOFC as conversion technology.

• EGS 2: Composed by the Micro-GT as conversion technology.

• EGS 3: Composed by the SOFC-MGT as conversion technology.

Actually, in the case of the EGS 1 and EGS 3 the SOFC should be changed one time

approximately at the middle (12th year) of those 20 years – as mentioned in previous section –

so even if they offer better performance this would be an extra cost that EGS 2 using only the

Micro-GT won’t have. On the other hand, the GCU of EGS 2 clearly would suppose an

important extra cost if compared to the CGU of the other systems, since removing CO2 for a

high-upgrade of biogas is expected to be quite expensive. Coming back to how is this study

focused on, it is important to remark that the economic analysis is divided in two parts:

1) A simple comparison between technologies: In order to know which of them would offer

a better economic performance in 20 years.

2) A deeper economic analysis for the selected technology: After choosing which is the

best option for Can Barrina (considering the results of the technical comparison and

preliminary results of the economic analysis) a more detailed assessment is needed.

Obviously, using part of the maize crops to feed the anaerobic digester might lead to

purchasing extra animal feed for the cows that are currently consuming this maize.

However, some years comes with better harvestings than expected, meaning less

monetary losses if less maize should be purchased that year. This affectation is

assessed only for the chosen technology, to avoid overwork.

Once this is clear, let’s start with the economic comparison between technologies.

8.1. Economic comparison between technologies

Clearly, independently of the conversion technology selected, all the installation of system in

charge of transforming the biomass and manure into biogas would have identical costs. In


other words, the mixing chamber, anaerobic digester, pumps, motors and so on would cost

the same no matter the conversion technology selected. Then, all the “basic” costs are listed

before analysing the individual costs of the conversion technologies. The next assumptions

are considered:

• The economic analysis won’t be a list of every single component and price composing

all the laborious and probably would not reflect the reality, because if this installation

was done by a real company those costs could vary from those that I can find, because

they would have access to many manufacturers offering various products and prices

in the wholesale market.

• The initial investment would be then determined by the approximate price that should

be payed to install mixing chamber, anaerobic digester, biogas storage tank, basic

GCU with tar and H2S removal (without CO2 removal since it would be only necessary

for EGS 2) and the price of each individual conversion technology (plus other specific

components listed later on). It would be considered the approximate price of the

different “blocks” or components and an approximate installation price.

• The biogas generation is assumed to be constant during the 20 years studied. Then,

biodigester’s cleaning processes described in section 5.1.6 are not considered to

interrupt the biogas production activity. The annual fixe costs would be then derived

from the normal operation of the EGS (salary of employees, constant operational costs

of the EGSs…); but they would differ depending on the EGS studied.

• The variable costs would vary depending the conversion technology used. Even if all

the expenses derived from the biogas production are equal for each EGS assessed, a

great impact on the variable costs would be derived from purchasing electricity and

diesel to supply unmet electrical and thermal demand, and this varies a lot depending

on the EGS.

Once this is clear, let’s start finding the costs for the most representative components. Starting

with the mixing chamber, it was found a price equal to 23919,49 € (material and installation)

for a biogas plant with a total anaerobic digester’s volume equal to 5185 m3 and a biogas

production 8,5 times larger than the one expected for this project [47]. This price includes the

concrete structure, agitation motor, manure spillway, separation layer – section 5.1.6 – and

associated pumps [47]. It is assumed that the system can be scaled down to the half, and so

the prices – meaning approximately a cost for the mixing chamber equal to 11959,25 €.

Regarding the anaerobic digester, the prices are usually given in function of volume of the

reactor or per cubic meter of treated manure. The price would depend on the volume of the

anaerobic digester, and for a 1200 m3 one is expected to be around 356,39 €/m3 for an annual

manure production of 9000 m3 [94]. Nonetheless, the anaerobic digester designed for this

Pág. 148 Report

project won’t be completely built from zero – remember that the already existing manure pool

number 3 should be used, section 5.1.6 – meaning that those cost would be considerably

reduced (following the previous reference, for a new anaerobic digester of the desired volume

it would cost approximately 384.901 €). Besides, the manure production is largely smaller than

the one of that study. With no extra thermal insultation, the same article says that covering a

pool of 1500 m3 would cost around 18000 € [94], however in this project two insulation layers

– special plastic and glass fibre – are used, being both quite expensive. It is assumed that

avoiding the excavation prices and the purchasing of the concrete needed to build the

biodigester’s structure would reduce the costs presented previously in a 60 %; meaning

153.960,4 € (installation, agitation motors, extraction valves and pumps, temperature and

quality control…). This would be the approximate amount also derived from scaling down the

prices for the plants presented in [43], [47].

The next essential component is the biogas storage tank. Those tans can be found easily, and

it has been selected one costing 9921 $ (approximately 8835 €) model Dalilpsg08 from the

company DALI [95]. The installation is assumed to cost an extra 1000 €, meaning a total cost

equal to 9835 € for the biogas storage tank (which included compressor, extraction and

entrance pumps, pressure control…).

Finally, the last basic “block” shared by all the studied EGSs is the mentioned part of the GCU

(the one described in section 6.2.1). Actually, the ZnO and ZnO/CuO beds described

previously would require the purchasing of some specific chemicals to trap H2S which are quite

expensive [96] – this method is known as chemical method. This GCU is would suppose an

investment estimated to be around 8700 € with an operation cost of 0,024 €/m3 of biogas

treated if chemical treatment is performed. However, the article Technical and economic study

of a full-scale biotrickling filter for H2S removal from biogas studies the viability of a specific

filter existing in the removal beds of the GCU that needs less chemicals to remove H2S;

resulting in lower operational costs equal to 0,013 €/m3 of biogas treated (considering the

biological treatment) [96]. Nonetheless, the investment for a GCU with this filter is much more

expensive (around 52000 €), resulting unattractive for a small EGS like the one sized in this

project – it would make sense to make the investment in large biogas plants of MW order.

Hence, the chemical method is chosen and the operation costs would be 1341,93 €/year for

the 55913,5 Nm3/year of biogas upgraded, with an investment of 8700 €.

These are the considered common investments for the EGSs assessed. In Table 8.1, Table

8.2 and Table 8.3 the commented investments are listed among the costs now explained: The

fixed costs (FC; don’t confuse with “Fuel Cell”) and variable costs (VC) derived from the

constant operation of the system; not including the FC and VC associated to the conversion


technologies. Let’s start determining those costs for operating all the EGS from the manure

and biomass recollection until the biogas production and H2S removal.

A) Fixed Costs:

Clearly, running this activity over the studied 20 years would mean having a lot of expenses in

operation and maintenance. For example; the harvesting, transportation and ensilage costs of

biomass, the salaries of the employees, the cleaning process of the biodigester carried out

every 4 years and so on can be assumed as FC because they are assumed to be equal each

year.

However, it is important to differentiate between the costs that are currently associated to the

normal Can Barrina’s activity and those new operational costs associated to the proposed

EGS. In example, the harvesting costs of biomass won’t change independently if this biomass

is used for biogas production or – as is currently used – as a nutritional component of the cow’s

feed. In other words, no extra costs should be considered for this specific case. This happens

for many other expenses, as a result, only the expected extra FC associated to the EGS

operation are presented now.

In section 5.2.1 it was assumed that the constant operation of the EGS might need a supervisor

working approximately 1 h/day (1 h in front of the computer with all the data and monitoring of

the system and another one supervising the correct supply of manure and biomass to ensure

the optimal operation of the system). Assuming a stipend of 10 €/h for that work it would mean

an extra FC of 7300 €/year. This stipend also covers the supervision of the conversion

technology.

Another important expense should be the cleaning processes of the anaerobic digester:

assumed to be 2000 € every 4 years. Besides, the 1341,93 €/year for the operation of the GCU

are also considered as FC. The mentioned FC are added to Table 8.1, Table 8.2 and Table

8.3.

B) Variable Costs:

Regarding the variable costs, the most significant ones are those associated to the energy

purchasing for covering the unmet demand: and this would change depending on the

conversion technology used. In next section, it would be assessed the affectation of the quality

of the harvesting period – which fluctuates depending on the year – for the chosen technology.

Let’s make each individual economic analysis for the three possible EGS taking into account

the FC and the investment already described.

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8.1.1. Economic study EGS 1

The price of a SOFC usually fluctuates between 1000-2500 €/kWe installed [81], [82] – as

mentioned in previous sections, this price have been reduced considerably in the lasts years,

since in 2013 this price could fluctuate from 3000-4500 €/kWe installed [69], [96], [76]. Actually,

1700 €/kWe as recommended in the Programme Review: Fuel Cells and Hydrogen Joint

Undertaking published by the EU [97]. Considering the nominal power of the SOFC of EGS 1

of 26,66 kWe, its price would be 45322 €. This price should be payed again in the middle of

11th year, and for the economic analysis is assumed to be paid at the beginning of 12th year.

Extra 15000 € are assumed to make all the installation of the SOFC, the heat exchangers and

the tubes used to transport the heat from the cell to the anaerobic digester and to the demand’s

location.

Another important consideration is that the SOFC produced the electricity in DC, usually having

a low voltage output [98]. Then, the help of a DC-AC inverter is essential to generate an AC to

provide the electricity to the loads and specially if it is wanted to be injected to the public electric

grid. For a 26,66 kW, and inverter of 30 kW of maximum power treatment is selected, the

model MA30KW from the company OEM, costing 4454 $ (~3926 €) [98]. This inverter would

be the same for the EGS 3, since the electricity produced by the SOFC in DC of that case is

the same than in this case, and the Micro-GT would produce directly in AC – so it is not

necessary to buy a larger inverter that allows higher power conversions. Finally, for the

calculations of the final electricity given by the EGS it is assumed that the inverter doesn’t have

losses.

The FC and the investment of this EGS is already known, and showed in Table 8.1; now the

saving must be determined. As mentioned before the electricity price in Spain was estimated

to be 0,156€/kWhe, while the diesel/gasoil for heating in a boiler 0,1€/kWhth (if a 90% efficiency

in the boiler is considered) [93]. Without EGS 20421,65 €/year are needed for covering the

electrical demand of Can Barrina (the new electrical demand of the biodigester is not included,

since the savings are only compared to the current demand) and 10150,93 €/year for covering

the thermal demand. With the existing demands in the farm; the annual expenses and direct

savings using this EGS are:

• Electricity: 4367 €/year should be to paid to cover the electrical demand. This means

that 16054,64 €/year would be saved in electricity.

• Diesel: The thermal demand is fully covered, meaning 10150,93 €/year saved in diesel.

Actually, the total saving of EGS 1 are 17825,07 €/year. It is important to remark that the


excess electricity is sold at Spanish electric price market – the mean electricity market price

from 2010 to 2019 has been 56,81 €/MWh [99]. With the excess electricity of EGS 1 seen at

Table 7.6 and the electricity selling price described 2750,01 €/year could be earned. An extra

700 € are added as FC to Table 8.1 as assumed taxes payed for injecting electricity to the grid.

The last appreciation made is that EU is funding a great fraction of the investment costs of

similar installations. In example, for the two plants assessed in the biogas report of IDEA a

40 % of the investment was paid by EU [43]. Actually, it wouldn’t make any sense making this

EGS without looking for the public subsidies given by the local administrations or governments.

Consequently, this reduction of the 40 % of the investment is considered, and it might be

actually more because is using a fuel cell technology.

EGS 1 Investment

Mixing chamber 11959,25 €

Anaerobic digester 153.960,4 €

Biogas storage tank 9835 €

Gas Cleaning Unit (no CO2 removal) 8700 €

SOFC 26,66 kW* 45322 € x 2 *

Inverter 3926 €

Extras 15000 €

TOTAL Investment* 294.024,65€ → 40 % reduction → 176.414,79 €

EGS 1 Fixed Costs

Operation EGS 7300 €/year

Cleaning of the anaerobic digester 2000 € every 4 years (starting year 5)

Gas Cleaning Unit operation 1341,93 €/year

Taxes for being generator in el. grid 700 €/year

TOTAL FC 9341,93 €/year + 2000 € every 4 years

EGS 1 Savings

Electricity savings 16054,64 €/year

Diesel saving 1770,43 €/year

TOTAL savings 17825,07 €/year

EGS 1 Economic Gains

Selling of excess electricity 2750,01 €/year

Cash Flow (total savings plus gains minus annual costs): 10733,79 €/year **

Table 8.1. Capital expenditure (CAPEX), Operation and Maintenance (OPEX), annual Savings and

annual Gains associated to EGS 1. (Source: Own).

* The SOFC would be replaced, so in a 20 years economic study it must be purchased two times. The

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Net Present Value at the end of the 20 years is calculated considering the purchasing of a new SOFC

in the 12th year.

** The 2000 € every 4 associated to the cleaning process of the biodigester years are divided as 500

€/year, in order to calculate the payback time. The Net Present Value at the end of the 20 years is

calculated paying 2000 € every 4 years, and then the annual saving varies depending on the year.

Once this is known, the payback time of the EGS 1 (tpayback_EGS1) can be calculated as showed

in Eq. 8.1.

𝑡𝑝𝑎𝑦𝑏𝑎𝑐𝑘𝐸𝐺𝑆1=

𝑇𝑜𝑡𝑎𝑙 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 (€)

𝐴𝑛𝑛𝑢𝑎𝑙 𝑠𝑎𝑣𝑖𝑛𝑔𝑠 𝑎𝑛𝑑 𝑔𝑎𝑖𝑛𝑠 (€

𝑦𝑒𝑎𝑟) (Eq. 8.1)

Assuming that the price associated to the replacing of the SOFC is directly summed in the

initial investment and the cleaning process is distributed identically over the years; the payback

time for the EGS 1 would be of 16,43 years. Without the SOFC replacement it would be 13,9

years, but this technology must be replaced.

The Net Present Value is also calculated assuming an interest rate (i) equal to 2 %. The

CashFlow is determined each year “n” with the annual savings for that year – plus the gains of

selling electricity – minus the VC and FC. Actually, all years are considered to be equal in term

of savings and costs except those with the biodigester cleaning process. It is interesting to

highlight that the investment for the same SOFC won’t “cost” the same in 12th years as it does

today. Applying the inflation also to the 45322 € of the SOFC it is obtained that (with a inflation

considered to be also a 2 %) the investment would be of 35736,09 € in 2032.

𝑁𝑃𝑉 = −𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 + ∑𝐶𝑎𝑠ℎ𝐹𝑙𝑜𝑤𝑛

(1+𝑖)𝑛20𝑛=1 (Eq. 8.2)

Applying Eq. 8.2, it has been found that the NPV after 20 years for that system would be equal

to -5,32 € (see the evolution in Fig. 8.1). From the economic point of view, this means that the

investment is not recommended since it would not generate benefits: NPV is negative. Even if

it is negative for so little, in this kind of projects the risk factor should also be taken into account,

for this reason some economists even do not recommend a large investment without the

security of a minimum amount of profits.

The same calculation has been performed with no interest rate – just to see if then it would be

positive – and it was obtained a NPV equal to 22119 €, but this is unrealistic since for paying

this installation it has been assumed that a mortgage would be pledged with a bank (and here

is where the interest rate appears). The conclusion is that this investment is – economically –


not recommended for EGS 1.

Fig. 8.1. Net Present Value after 20 years of EGS 1, with inflation rate of 2 %. (Source: Own).


Let’s start with the investment of this EGS based on the Micro-GT as conversion technology

knowing that all the costs related with the anaerobic digestion installation does not change.

Then, the cost of the SOFC and the extras associated to it wouldn’t be paid in this scenario.

The first extra investment associated to this conversion technology is the added CO2 removal

technology – remember that chemical scrubbing with amine solutions was performed, Fig. 6.4

– which is estimated to cost 2000 € [100] and 72$ (63,76 €) for ton of CO2 removed [101]. At

the end of the year around 51,2 tonnes of CO2 would be removed, supposing an extra expense

of 3264,5 €/year.

Finally, the conversion technology is much cheaper if compared with the SOFC. The Micro-

GT of Capstone Turbine ModelC20 would cost around $700-$1100/kWe (619 € - 973 €/kWe)

with an extra costs of 30-50 % to the total Micro-GT cost added for the installation of the

components of the gas cycle [102]. Supposing a cost of 750 €/kWe the investment for the gas

cycle components would be equal to 15000 € (20 kW Micro-GT) plus 6000 € of installation

(40 % of the cost of the turbine). Besides, it won’t be replaced since the lifetime of a turbine

would be, at least, larger than the studied 20 years.

Regarding the savings and gains of electricity and heat with EGS 2:

• 7077,01 €/year are saved in electricity.

-160000

-140000

-120000

-100000

-80000

-60000

-40000

-20000

0

0 5 10 15 20 25

Net

Pre

sen

t V

alu

e (€

)

t (years)

NPV of EGS 1

Pág. 154 Report

• 1770,42 €/year are saved in diesel.

• Extra electricity (that cannot be used when produced) can be sold for 365,11 €/year

(same electricity market prices than for EGS 1).

Table 8.2 shows the same comparison between economical expenses and saving showed in

Table 8.1, but in this case for EGS 2. Since the 365,11 €/year that could be sold in form of

electricity are lower than the assumed taxes, the system won’t inject and sold the excess

electricity. The same percentage of subsidies (40 %) as before is applied to the initial cost of

the system.

EGS 2 Investment





CO2 scrubber 2000 €

Micro-GT 15000 €

Installation gas cycle 6000 €

TOTAL Investment* 207.454,65 €→ 40 % reduction → 124.472,79 €

EGS 2 Fixed Costs



Gas Cleaning Unit operation* 1341,93 €/year + 3264,5 €*


EGS 2 Savings




Cash Flow (total savings plus gains minus annual costs): - 3058,99 €/year **



* The cost of removing CO2 are summed.

** Same as previous case.

The investment on this technology won’t be feasible at all, since the operational and


maintenance costs are larger than the savings. In reality, if the stipend of an employee working

the required hours in the system is not considered it would give even positive results, but in a

realistic economic study this expense must be taken into account. Consequently, the NPV is

not even calculated because it is known beforehand that the investment in EGS 2 is not

recommended at all and the money invested would never be recovered.


Finally, the economic analysis of the EGS 3 with the SOFC-MGT conversion technology

performed. Clearly, in this case the price per kWe installed would go down if compared directly

with the SOFC alone: Because the other technology used is less expensive than the fuel cell.

However, the amount of kWe that can be delivered using the same SOFC would also increase.

As a matter of a fact, multiple references give different prices for this kind of systems, from

around 750 €/kWe up to 2500 €/kWe installed [91], [103]. The specific price for the installed

RRFCS of 34,91 kWe was not found, especially because it a recuperator and a cathode blower

instead of an ejector was desired to be installed to increase the efficiency. Consequently, the

investment associated to this technology is now approximated by calculating the individual

price of the main components.

The SOFC of RRFCS can be assumed to have the same price than the one estimated for the

SOFC of Wärtsilä Findland used in EGS 1: 45322 €, because the power output would be

approximately the same. The Micro-GT composing the system of RRFCS has 15 kW nominal

power – smaller than the one EGS 2 – because it’s using only the exhaust gases and not

directly the biogas. The same price per kWe can be assumed, resulting in 11250 €. Adding

heat recovery augments the cost of the conversion technology in $75-$350/kWe (66,4 € - 310

€/kWe) of nominal power of the Micro-GT [102]. Assuming 200 €/kWe of nominal power of

Micro-GT it supposes extra costs of 3000 €. The same inverter DC-AC of EGS 1 can be used

in this case (only the electricity generated by the SOFC needs to be converted). Summing all

these prices, the material investment would be equal to 63498 €.

In this case cost of 21000 € (summing the ones for the conversion technology of EGS 1 and

EGS 2) are considered. It must be taken into account that the SOFC would be replaced as in

EGS 1 at the middle of the 11th year. The rest of the components of the SOFC-MGT system

would not be replaced, because their lifetime is larger than 20 years. Therefore, 45322 € would

be counted at the beginning of 12th year while calculating the NPV of this study-case (it makes

sense to account only the price of the technology and not add the installation costs, because

more or less compensates the rapid cheapening effect that are experiencing the SOFCs).

Table 8.3 shows the same economic list made for EGS 1 and EGS 2 for this case. Again, 40 %

of the investment is expected to be paid by public subsidies.

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EGS 3 Investment





SOFC 26,66 kW* 45322 € x 2 *

Inverter 3926 €

Micro-GT 11250 €

Installation costs of the SOFC-MGT 21000 €

TOTAL Investment* 314.274,65€ → 40 % reduction → 188.564,79 €

EGS 3 Fixed Costs



Gas Cleaning Unit operation 1341,93 €/year

Taxes for being generator in el. grid 700 €/year


EGS 3 Savings




EGS 3 Economic Gains

Selling of excess electricity 5802 €/year

Cash Flow (total savings plus gains minus annual costs): 16592,37 €/year **



* Same as in EGS 1

** Same as in both previous cases.

In this case, the Cash Flow is the most favourable of all the EGSs analysed. Applying Eq. 8.1,

it is obtained a payback time of 11,36 years (5 years faster than EGS 1). Besides, applying

Eq. 8.2 the NPV with the same interest rate is calculated resulting in 83651,35 € at the end of

the 20th year (see the evolution in Fig. 8.2). Consequently, this investment is highly

recommended considering the boundary conditions of the economic study performed until

now.


From the three alternatives studied the SOFC-MGT system as conversion technology offers

without any doubt the best results technically and economically. For this reason, this has been

the selected EGS for this project, and from now on the rest of the project is performed only

with EGS 3.

Fig. 8.2. Net Present Value after 20 years for EGS 3, with inflation rate of 2 %. (Source: Own).

8.2. Detailed economic analysis for the EGS 3

Once the most suitable conversion technology was found, it was the time to evaluate in detail

the economic analysis in order to find if there is any extra cost that may fluctuate depending

on the year for the selected EGS. In fact, there is an important parameter that hasn’t been

taken into account in the previous economic analysis since the mere objective of those analysis

was determining which was the best EGS from the proposed ones: and it is the cost of the

biomass used in the biodigester.

Before assessing this, the same NPV evolution showed at Fig. 8.2 is represented again in Fig.

8.3 but considering a 40 % reduction for the price of replacing the SOFC. In the previous case

only a 40 % reduction was considered for the three EGSs studied only applied to the initial

investment; but it makes sense that this public subsidy also covers the replacement of the fuel

cell. As it may be seen the NPV would be then 94922,42 € (meaning an extra benefit of

11271,07 € after the 20 years studied).

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Fig. 8.3. Net Present Value after 20 years for EGS 3, with inflation rate of 2 % and with 40 %

reduction in SOFC replacing price. (Source: Own).

Regarding the biomass introduced before, it is vital to remember that only plants produced in

the same farm were considered as possible feeding organic matter for the anaerobic digester;

and after analysing the performance of the various cereals cultivated in Can Barrina every

year, maize was the one offering best results when mixed with manure for producing biogas

(so it provides the higher biogas yields). However, there is a clear drawback of using 226,5

tmaize/year (calculated in section 5.4.1) for producing biogas; and it is the price that should be

paid for buying the same amount of this cereal for producing the cow feed.

As displayed in Table 4.1, the amount of harvested maize varies depending on the year

between 850 and 3000 tonnes of maize (being the best and worst year registered). The

demand of maize can be considered as constant every year and equal to 1020 t/year:

Balancing with the cows’ diet showed at section 5.1.3 the estimated maize consumption for

that purpose.

The most realistic economic analysis would be one where, when the production of maize is

large enough to cover the maize demand to feed the 251 adult cows plus the demand of the

biodigester (1246,5 t/year), the economic expenses of using part of the harvested maize to

feed the anaerobic digester can be assumed to be zero. On the other hand, if the harvested

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maize is not enough, every tonne of the 1246,5 t/year not would cost around 50-60 €/t (price

of fresh siled maize given by Eduard) – actually, 50 €/t are assumed because the cheapest

biomass should be used if it is for putting some of them in the biodigester. It was though an

alternative where only the plant of the maize – the cheapest part – is used for producing biogas

(using the corn only to produce cow feed), but actually separating the plant from the corn in a

fresh maize silage might be even more expensive than the 50 €/t exposed by the farm’s owner.

Moreover, according to the Eduard the production of maize is typically nearer to the minimum

production than to the maximum one: And those 1246,5 t/year would be expected to be

covered 2 out of every 5 years (the half of the years they can neither cover the 1020 t/year

currently demanded to produce all the cow feed). Since there is a tremendous variability in the

maize’s production; two scenarios are proposed:

1. The price of replacing 226,5 tmaize/year would be payed 3 out of 5 years meaning 11325

€/year the first, second and fourth year (assuming that in the 3rd and 5th year there is

excess production). In this case the excess production for those years is not used.

Including these costs in the economic analysis affects affect the NPV for EGS 3 like

displayed at Fig. 8.4. In this case, the NPV would be negative and equal to – 10889 €.

Thus, the investment would not be recommended (economically) in that case.

Fig. 8.4. NPV evolution for selected EGS and lack of maize 3 out of 5 years (40 % reduction in SOFC

replacement price). (Source: Own).

2. In this scenario the excess maize in years with overproduction is used for the next year

(it is what happens in Can Barrina currently, because as it was said there is the

uncertainty of having all the maize production that is required to feed the cows without

the need of purchasing extra crops from external sellers). In that case, the exact

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production expected for each individual year remains a clear incognita. Since it cannot

be known, the maize production for each of the 20 years studied is calculated

randomly, knowing that there is a 40 % of possibilities – following this criterion of excess

harvested maize 2 out of 5 years – of being larger than the required one. To do so, the

“randomize” function of Excel is used to obtain values between 0 and 100 and those

between 0 and 40 are arbitrary selected as years with excess production – another

range could have been taken, but maintaining the probability of 40 %. For those years

with excess production, a value between 1246,5 and 2500 tonnes of maize are

designed again with the “randomize” function – the upper limit has been put at 2500

tonnes of maize because harvesting larger quantities is extremely rare according to

Eduard.

The result is may vary depending on the simulation because the annual production

would be determined full randomly for the 20 years (as it happens in reality, they never

know how good would be the year since it depends directly on meteorological

conditions). Thereupon, infinite results can be expected: positive NPV and negative

ones, depending on how good are the harvesting periods. It is important to remark

again that the excess maize is used for the next years in this scenario. For example,

Fig. 8.5 shows the first simulation that was obtained the first time this Excel sheet was

run. On the other hand, Fig. 8.6 shows the second simulation for this same case.

Fig. 8.5. NPV of the first simulation of scenario 2. (Source: Own).


Fig. 8.6. NPV of the second simulation of scenario 2. (Source: Own).

From the two previous scenarios clearly the second one is the one that adapts better to the

reality, an uncertainty for the NPV (and so the payback time) for the installation of this project.

There is a real dependence on the “luck” or “fortune” to ensure the amortization and large

benefits expected from this installation. The previous two simulations are shown among three

others in Fig. 8.7, to compare how the results can change depending on the variability of the

maize’s production.

Fig. 8.7. NPV for the first five simulations carried out for scenario 2. (Source: Own).

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Simulation 1 Simulation 2 Simulation 3 Simulation 4 Simulation 5

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The results associated to those simulations are:

• Simulation 1: NPV equal to 20010,36 €

• Simulation 2: NPV equal to -8620,83 €



• Simulation 5: NPV equal to -23569,07 €

Which of those result is better? Actually, all the results of the 5 simulations are equally correct,

all of them can be the real results depending on the harvesting periods of maize for the 20

years studied. This leads to a clear conclusion, there is the risk of not amortizing the EGS even

if there is a high possibility of doing it so. Besides, in the best case almost 100.000 € can be

obtained as benefit after 20 years.

The decision should be taken by the farm’s owner, and if this risk is worth it or not (even if there

could be economic helps in case of monetary loses since it might be a benchmark project in

Europe would depend on public subsidies’ characteristics). To sum up, if this risk is something

that the client is willing to cope with, the investment is clearly recommended from the technical

point of view, but not from the economical (the risk is too high). This explanation is extended

in the project conclusions.


9. Environmental analysis

In this section the environmental analysis over 20 years that would be performed by the

selected EGS is assessed. It is important to say that only the direct savings of CO2 associated

to the system are studied, and the deep Life Cycle Assessment (LCA) of the different

components is considered to be out of the scope of this project: In other words, the emissions

associated to the obtention of the materials (mining, transportation…) and for the

manufacturing/fabrication of all the individual components of the EGS (anaerobic digester,

SOFC, Micro-GT, pumps…) are not taken into account. Nonetheless, analysing briefly LCA

already carried out for SOFCs and anaerobic digesters it can be seen that, even if the intensive

fabrication process derives in high emissions, it is a cleaner technology if compared to the

current conventional energetic systems [105].

Before analysing the environmental effect of covering part of the electrical and thermal demand

of Can Barrina with a renewable system, the emissions of CO2/kWh associated to this EGS

should be calculated or justified. In fact, biogas is described as a renewable energy and a

green technology with environmental benefits. Even if in the proposed EGS the CO2 part

supposes a 30,6 % of the biogas (as said in Table 5.7), and more CO2 would be generated

after the steam reformation of methane to produce the hydrogen that the SOFC would use;

this gas is considered clean and to have an almost neutral environmental impact [106]–[108].

Why is this consideration made?

The fist point is understanding that biogas is considered renewable because it can be

generated with an “unlimited” energy source (this source would exist as long as the manure of

livestock can be collected and crops harvested) by a biological method as it is anaerobic

digestion – differing from other similar products like NG which is produced in long term

geological processes; making it a limited resource [108]. Moreover, if biogas is produced in a

co-digestion process with biomass and manure [43], [107]:

• The amount of CO2 captured by the biomass by the photosynthesis process is then

reduced from the CO2 emissions associated to the conversion technology which uses

this biogas: Hence, it is considered as biogenic carbon dioxide. It is a similar concept

than the one used for assessing the environmental impact of burning biomass at it

could be wood pellets, considered as a renewable energy with almost neutral emission

for that compensation effect [107].

• Most important, when assessing the positive impact of biogas generated with cattle

manure and biomass it is always taken into account the reduction of uncontrolled CH4

emissions derived from the storing of manure in pools. Indeed, the slurry storage rafts

used in farms emit a tremendous amount of CH4 with a Global Warming Potential

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(GWP) 21 times higher than the same amount of CO2 ([43], [107]); carbon dioxide that

would be emitted later during the normal operation of the EGS if not captured.

Therefore, if this slurry is controlled inside the anaerobic digester this CH4 emissions

– generated by the same slurry – can be avoided, mitigating the negative effects of

releasing this GHG into the atmosphere.

Actually, in the article Environmental impact of biogas: A short review of current knowledge

[107]; it is highlighted that usually biogas gives a negative CO2 balance because the carbon

dioxide capture/mitigation results, in absolute terms, higher than the feedstock supply and

emissions released by the EGS (considering that this CO2 is not sequestrated by any of the

methods explained in section 7.2.3). Providing that this GHG is sequestrated, this absolute

value of the CO2 balance would be even more negative; meaning better environmental impact.

In fact, the same article commented the GHGs savings for 10 different biogas plants producing

electricity and heat (but using this biogas in a large CHP plant with gas cycle); reaching the

conclusion that for those plants 85 to 251 gCO2/kWhe were emitted but at the same time there

was a GHG saving of 2,31 – 3,16 kWhfossil/kWhe if compared to a conventional plant. Besides,

this emissions were fully compensated by the CO2 captured by the biomass used to produce

this biogas [107].

Since it is difficult to quantify the exact amount of equivalent CO2 avoided by the proposed

EGS during 20 years, it would be assumed that GHGs would be mitigated only by:

1) The CO2 savings by the electricity produced by the EGS and the thermal heat covered

from Can Barrina’s demand.

2) The CH4 (calculated in equivalent CO2) saved by the co-digestion process carried out

in the anaerobic digester – instead of storing the slurry in slurry storage rafts.

On the one hand the savings produced by the direct electricity and heat generation performed

by the EGS can be easily obtained by comparing the CO2 production with the EGS and those

associated to the current methods used for supplying the energetic needs of the farm. For the

reasons recently commented, it is assumed that the CO2 is not captured (CCS is expensive

and has not been included in the economic analysis) but at the same time there is neutral CO2

emissions for kWh of biogas consumed.

Hence, the total CO2 saving relies on the amounts that would be released into the atmosphere

if the EGS was not installed. To do so, it has been assumed that for the 20 years the Spanish

Electricity Mix emits 241 gCO2/kWhe purchased [109] – obtained from the “Departament de


Cani Climàtic de la Generalitat de Catalunya”. Moreover, with the heat demand covered by the

EGS the diesel consumption will go down. For diesel burned in a boiler (90% eff.) it can be

assumed to be released 2,67 kgCO2/Ldiesel [110], and with the LHV of 9,98 kWh/ Ldiesel [111],

emissions of 0,2675 kgCO2/kWh can be assumed. Consequently, the following results are

obtained:

• 53,89 tCO2/year are avoided thanks to the 223.605,23 kWhe/year generated by the

EGS (from which 121.475,21 kWh/year are self-consumed in the farm and 102.130

kWh/year are injected to the public grid).

• 4,5 tCO2/year are avoided thanks to the 16821,61 kWhth/year self-consumed in the

farm.

• From the electric side the remaining 822210,56 kWhe/year are destined to the

anaerobic digester operation, and this won’t generate any savings if compared to

the current situation; since this installation does not exist in Can Barrina today and

it is a new demand. The same happens with the heat derived to this device.

Moreover, the excess heat cannot be counted to generate carbon dioxide saving

because it would be wasted energy.

From this side, a total of 58,39 tCO2/year are avoided (results added in Table 9.1)

On the other hand, the VS portion of manure would generate CH4 if slurry is stored in a pool a

storage raft, although the methane production yield would be much lower of that achieved in

the anaerobic digester (obviously). According to the article Greenhouse gas emissions from

liquid dairy manure: Prediction and mitigation [112], after some months of having the cattle

manure (in that case poultry, dairy and pig manure) in an open pool for 7 months at

approximately 20 ºC, the 50 % of the TS was degraded with a “significant loss of labile VS”

which means that CH4 among other gases was emitted. The degradation process works in a

similar way than in the co-digestion process, with microbial populations in this case developed

in surface crusts (with CH4 oxidizing bacteria). The same article remarks that the “Danish

national inventory for agricultural GHG emissions” calculated a 41 % reduction of methane

emissions if an anaerobic digester is used. With this percentages (and the TS and VS

estimated for calculating the biogas production) it can be calculated the expected CH4

emissions for a storage pool like the one existing in Can Barrina and then the saved emissions

(considering a 41 % reduction [112]):

• 10,92 tCH4/year would be emitted with all Can Barrina’s manure stored in a pool as it

is currently done. Considering the GWP of methane – 1 kg of CH4 has the same

negative impact than 25 kg of CO2 [113] (and not 21 as proposed in [106]) – the CH4

emissions associated to Can Barrina’s manure storage pool ascends to 272,88

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tCO2eq/year.

• With the 41 % reduction associated to the anaerobic digester activity this means that

111,88 tCO2eq/year are saved (results added to Table 9.1).

Finally, all these saving are showed in Table 9.1 to visualize clearly the impact of each activity

that reduces the current CO2 emissions of Can Barrina. Besides, the total equivalent tonnes of

CO2 saved after 20 years of operation of the EGS are added.

Saving for a standard year

Activity from which CO2 is saved Saved carbon dioxide (tCO2eq/year)

EGS electricity production 53,89

EGS thermal production 4,5

Anaerobic digestion (substituting storage pool) 111,88

TOTAL savings per year 170,27

Savings after 20 years

TOTAL savings after 20 years 3405,4 tCO2eq

Table 9.1. Saved CO2 emissions by the EGS yearly and after 20 years. (Source: Own).


Conclusions

In this section, the final conclusions extracted from the developing of this project are exposed:

Dividing them into personal conclusions and into conclusions of the project itself.

Personal conclusions

Personally, elaborating this project has supposed a great challenge in terms of time, effort and

dedication. The most important outcome that I extract from developing this Master’s Thesis is

the experience gained by applying the knowledge and personal skills acquired throughout the

two years that I have attended this Master’s Degree in Energy Engineering (specialization in

Renewable Energies).

Not only have I tested those skills, but I have had the opportunity to inquire profusely and

deeply in a very interesting – and yet almost unexplored – sector that has a tremendous

potential to grow and improve: The usage of agricultural and branch residues for generating

energy. Consequently, a wide range of new concepts on the field of characterization and

monitoring of energetic needs of a super-structure, chemistry, energetic balances and self-

consumption systems have been gained as personal reward. I reckon that these concepts

could be very useful for future projects in my professional career.

Conclusions of the project

It is considered that the objectives proposed at the beginning of this project have been

accomplished successfully.

After studying deeply Can Barrina’s demand to obtain the electricity and thermal needs of the

farm for each hour of a standard year, the perfect size for an anaerobic digester as well as its

biogas production have been obtained; also taking into account the available cattle manure

and biomass produced as wastes/resources. Regarding this co-digestion process, only the

liquid manure should be used to avoid monetary losses by stopping a current lucrative activity

carried out in the farm: the selling of fertilizers. Besides, among the cultivated cereals maize

arises as the best alternative to be mixed with manure to produce the biogas, boosting

methane production yield (using another biomass would imply a retrogress). The anaerobic

digester should be installed using the existing infrastructure of the manure storage pool

number 3 to avoid extra unnecessary installation costs – if liquid manure is used to produce

biogas the storage pools won’t be needed anymore.

Regarding the conversion technology used to transform the produced (and upgraded) biogas

into electricity and heat, the usage of a SOFC with a Micro-GT using the exhaust hot generated

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in the normal operating of the fuel cell is the best option technically, economically and

environmentally. The problem with the MCFC is that is more expensive and, for a “small-size”

farm the as Can Barrina, the (little) efficiency gains are not expected to return the overrun of

this technology if compared to the SOFC.

Technically, an EGS with a conversion technology based uniquely on a SOFC has the problem

of lower electricity coverage and too much excess thermal energy, that would be thrown away

– since there is no more demand near the farm and building infrastructure would be really

expensive. Likewise, using a gas cycle with a Micro-GT would be quite inefficient since at

small-scale turbines their efficiency drops considerably if compared to larger systems, resulting

in low electrical efficiency for converting the biogas into electricity. For the selected EGS, the

electrical demand of the farm plus the new electrical requirements of the biodigester would be

covered in a 95,57%, resulting in a self-consumption of a 92,72 % of the current electrical

demand of the farm (and large amounts of excess electricity that should be injected to the

public grid and sold). Besides, the generated heat would ensure the uninterruptedly operation

of the anaerobic digester and would cover the current thermal demand in a 95,01 %.

Economically, the anaerobic digester takes over the vast majority of the initial investment,

conditioning a lot the importance of the self-consumption coverage offered by each conversion

technology for amortizing the installation. Without taking into account the variability of the

harvests of each year, only the systems with a SOFC can become economically feasible. In

the case of the gas cycle the operation costs associated to the CO2 removal needed to upgrade

the biogas into almost pure biomethane – needed to run the cycle securely – make that

investment an economic failure. The installations based on a SOFC as conversion technology

would only be amortized if:

• Around 40 % of the installation costs are covered by public subsidies (usually given by

IDAE or ICE to similar renewable installations).

• The agricultural exceeds of autumn harvesting periods from the years with

overproduction of maize are enough to cover the lack of production expected for the

60 % of the years (generating monetary losses associated to the purchasing of maize

that would be then required). The existing uncertainty in respect this matter adds a

considerable economic risk when evaluating if the investment is judicious or not, even

if after analysing multiple simulations the majority of them led to positive economical

results after 20 years.

Environmentally, there is no doubt that the installation of this system would suppose a

tremendous reduction of pollutant emissions (CO2 and CH4 basically). In this case, not only


are these emissions mitigated by the self-consumed electrical and thermal energy using a

green resource instead of the conventional ones, but especially a great reduction of the

methane released due to accumulation of manure in a slurry storage raft would occur.

Moreover, the coproducts of the co-digestion process are basically fertilizers that could be

used as natural dressing to aid production of crops. Thereupon, the carbon footprint of the

farm and its long-term sustainability would be boosted considerably – even more if a CCS

technology if implemented, even if it is not recommended providing that economic amortization

was prioritized.

To sum up, the implementation of the proposed system could endow a wide range of energy

independence to the farm. This would have been another project than the studied one; but

installing a cheaper electrical generation technology in the farm to cover its demand (as PV

solar panels) combined with the same co-digestion process might also be assessed as an

interesting alternative (in that case biogas would be directly upgraded and sold). I personally

recommend looking for various alternatives because surely more than one offers economic

gains after a reasonable period of time while improving a lot the “eco-friendliness” of Can

Barrina.

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Acknowledgements

Fist of all, I would like to thank the director of this Master’s Thesis, Jordi Llorca Piqué, for all

his support, advices and recommendations given during the developing of this project. His

readiness and feedback have been vital to give this project the reached level of accuracy,

detail and professionalism.

I could not be more grateful to Can Barrina’s owner, Eduard Vila, and his brother, Albert Vila,

who gave me full access to all the information, data and facilities of Can Barrina. Without them,

this project would have never been possible. They were available all the times that I asked for

specific information or their priorities (just as a reminder, this project aims to suit optimally to

their interests and needs since they are “the client” of this study). For this reason, I congratulate

them on running the farm so well and I wish this project helps them to assess if an Energy

Generation System as the proposed one could be interesting for their wills.

Finally, I would like to thank also the energy engineers Eric Coll, Pol Hodaly and Andreu Nadal

for developing together the bases of this project in the first semester of 2019 (of this Master’s

Degree). The ideas we came up with together for developing a short project have been

extended to a Master’s Thesis; since there was a lot to improve and to study in deeper detail.

I believe that we share equally the merits of the bases of this project.


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