energy modelling in gabi 2018 edition€¢input options of the hydro power lca ......

Energy modelling in GaBi

2018 edition

Oliver Schuller (Dr.-Ing.)

Principal Consultant and Team Lead

“Oil & Gas” and “Energy & Utilities”

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1. Overview electricity model

2. Individual modules – energy carriers

3. Individual modules – energy conversion

4. Electricity mixes

Agenda

Environmental assessment

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Extraction &

Production

Transport

Conversion

Transmission & Distribution

of energy supply chains

Energy systems / generic modelling

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To provide a comprehensive range of LCI data sets, a large amount of data has to be handled

How do we handle large amounts of data and generate consistent datasets?

Challenge

Approach

Development of a model, which allows the adaptation to various

country- and technology- specific boundary conditions

Generic, parameterized, adaptable models

Source:

http://visibleearth.nasa.gov/

Energy generation (fossil) - example

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Fuel parameter

• Calorific value

• Carbon content

• Sulphur content

• etc.

LCI

• Auxiliary materials

• Emissions (CO2, NOx)

• Waste heat

Conversionparameter

Energy Conversion Unit:

• Plant type (direct, CHP etc)

• Combustion technology

• Efficiency

• Type of cooling system

• Flue gas cleaning

technologies

• Allocation method

Parameterized models – electricity grid mix

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TransmissionPower

Grid Mix

Hard coal power plant

Lignite

Coal gases

Heavy Fuel Oil (HFO)

Natural Gas

Biomass power plant

Biogas power plant

Waste incineration plant

Photovoltaic units

Wind Converter

Nuclear power plant

Hydropower plant

Supply of coal gases

Natural gas supply

Uranium supply

Biogas supply

Waste supply

HFO supply

Biomass supply

Hard coal supply

Lignite supply

Parameterized models – electricity grid mix

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Hard coal

(Country A)Hard coal

(Country A) Hard coal

power plant Tra

nsm

issio

n

Imported Electricity

System boundary

Energy carrier

production

Electricity conversion

(production & transmission)Energy carrier transport

and mix

Hard coal

Country A

Natural gas

power plant

Transports

(Country A)

Natural Gas

(Country A)Natural Gas

(Country A)Natural Gas

Country A

Transports

(Country A)

TransportTransport

Country An

TransportTransport

Country An

.........

Mix

Mix

Conclusions

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• Generic models offer the adaptability to various country and boundary conditions

micro, macro and global level

• Results are comparable due to consistent approach and system boundaries

• Allows comprehensive LCI, LCIA, carbon footprint and water footprint analysis

• Complex models with a large amount of data, but reduced number of key parameters

are easy to manage and adapt

• High quality data with acceptable time effort reduces costs

• Supports scenario modeling and outlooks

• Creating, maintaining and updating the GaBi databases since 1990

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Agenda

Crude oil & natural gas supply chain

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Crude oil / natural gas production

Crude oil / natural gas transport

Crude oil refining (downstream)

Crude oil / natural gas consumption mix NG

Refinery products

Crude oil

Crude oil & natural gas - production technologies

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Crude oil production technologies

Primary crude oil

production

Secondary crude oil

production

Tertiary crude oil

production (EOR)

Conventional crude oil

production technologies

(onshore, offshore)

Unconventional crude oil

production technologies

(onshore)

Oil sands(in-situ, open-pit)

Oil shale(in-situ, open-pit,

underground)

Steam injection

Nitrogen injection

CO2-Injection

Natural gas injection

Solvent injection

Crude oil production – GaBi screenshot

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Mechanical energy

Thermal energy

Electrical energy

Flaring and ventingRessources

Waste water and

waste

Main unit process

(production and

processing)

Crude oil & natural gas production –

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• Calculation of energy consumption depending on:

• Reservoir depth

• Water-oil-ratio (at well)

• Steam-oil-ratio and steam quality (if any)

• Amount of injected media (water, steam, etc.)

• Efficiency (pumps, generators etc.)

• Quality of natural gas (concentration of water, H2S, CO2)

• Data from literature for:

• Flaring and venting rates

• Solid waste

• Waste water

• Share of onshore-/ offshore-production

• Produced amount of crude oil/ natural gas/ NGL (allocation according to net calorific value)

model parameters

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Technology used (primary, secondary, tertiary production)

Energy supply (source / efficiency / type of conversion)

Share of produced crude oil, natural gas and NGL

Drilling / reservoir depth

Water-oil ratio

Flaring and venting rates

Share of onshore / offshore production

Crude oil & natural gas production –

model parameters


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Refinery products

Crude oil

Crude oil consumption mix – GaBi screenshot

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Country-

specific

production

International

transportationParameterized

mixing process

National

transportation

………

………

………

Crude oil & natural gas consumption mix –

key parameters

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Consumption mix by country of origin

Transport type (pipeline, tanker, LNG tanker)

Transport distances

Distribution losses

Efficiency and distances between compressor stations (pipeline)

Energy supply of compressors (pipeline)

Crude oil & natural gas consumption mix –

main data sources

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• Mix information based on International Energy Agency (IEA) statistics

• Transport distance from literature and web calculators

• Tanker vessel and pipeline models in GaBi


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Refinery products

Crude oil

Crude oil based fuels

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Crude oil

Natural gas (for

energy supply/

H2 production)

Methanol / Ethanol

(octane number

increase)

Electricity

Water

Crude oil

refining

Products

Emissions

Waste water

Hydrogen

Inputs and outputs

– refinery system boundary

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• Petroleum refineries are complex plants.

• The combination and sequence of the processes is usually very specific to the

characteristics of the crude oil and the products to be manufactured.

• Due to the interlinkages within the refinery, all refinery products have to be considered.

• What technologies and processes are used within the refinery?

• Possible approaches regarding level of detail of analysis:

• Refinery as black box model

• Detailed refinery analysis (every single process)

• Hybrid approach

• Level of detail in dependency of scope, level of data availability, etc.

Every refinery is individual


– refinery system boundary

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InputsOutputs

Main unit

process –

mass

balance


– Refinery GaBi screenshot

Crude oil based fuels – Refinery GaBi screenshot

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Inputs

Outputs

Complex models for the calculation of environmental profiles can be set up and managed

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• Method:

• Detailed modeling of the refinery mass and energy balance

• Emissions of the total refinery (black box) are allocated to the products

• But allocation factors are modeled precise (due to detailed mass & energy balance)

• Consequence:

• Clear, relatively precise, but no environmental analysis of single processes possible

• Which data are required?

• Input and output flows of refinery

• Output spectrum, i.e. 20% diesel, 10% naphtha, 30% gasoline, 2% refinery gas,…

• Amount of purchased energy from external sources (outside refinery)

• Process capacities (incl. utilization) of each process

detailed flow chart including figures to model the mass balance

• Environmental impacts, i.e. emissions of the whole refinery (black box, bubble)

• Feedstock and product properties (net calorific value, sulphur content,…)

• Energy demand of each single process


– refinery approach

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Agenda

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Fuel parameter

• Calorific value

• Carbon content

• Sulphur content

• etc.

LCI

• Auxiliary materials

• Emissions (CO2, NOx)

• Waste heat

Conversionparameter

Energy Conversion Unit:

• Plant type (direct, CHP etc)

• Combustion technology

• Efficiency

• Type of cooling system

• Flue gas cleaning

technologies

• Allocation method



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Basis for all combustion models

• Efficiency, share of CHP/direct, own consumption

• Data is calculated based on statistics and directly used in the power plant models. Data sources:

• International Energy Agency (IEA), Electricity Information, Paris, France

• International Energy Agency (IEA), Energy Statistics of Non-OECD Countries, Paris, France

• International Energy Agency (IEA), Energy Balances of Non-OECD Countries, Paris, France

• Emissions

• Relevant emissions (CO2, CO, NOX, SO2, dust, NMVOC, N2O, CH4, Dioxin) are derived country-specific from literature/databases. Data is used directly and partly indirectly (used to determine e.g. efficiency for desulphurization or dedusting in the model. Data sources:

• European Environment Agency (EEA): Plant-by-Plant emissions of SO2, NOX and dust and energy input to large combustion plants

• National Inventory reports (CO2, CH4, N2O)

• For complete list compare provided Excel file


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Basis for all combustion models

• Emissions

• Other emissions like heavy metals, consumption of air, water in flue gas etc. are calculated based on combustion calculation and fuel properties:

• F. Brandt: Brennstoffe und Verbrennungsrechnung, 2. Auflage, 1991

• DGMK - Deutsche wissenschaftliche Gesellschaft für Erdöl, Erdgas und Kohlee.V.Ansatzpunkte und Poteniale zur Minderung des Treibhauseffekts aus Sicht der fossilen Energieträger - Forschungsbericht

• EIA - Energy Information Administration (US Energy department): C.5 Gross Heat Content of Dry Natural Gas Production, 1980-2004 & C.3 Gross Heat Content of Crude Oil, 1980-2003, 2005 (Oil & gas)

• 20 additional literature sources

• Energy input

• Input of energy carriers is calculated based on efficiency, allocation and NCV of energy carrier

• Waste/secondary products (bottom ash, fly ash, gypsum etc.)

• Calculation based on fuel properties and combustion calculation (transfer coefficients)

Hydro power plant

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• Run-of-river plants

• Production of base load electricity from hydropower

• Efficiency η ≈ 93 %

• Low-pressure plant (low head)

• Kaplan-turbines

• Storage plants

• Production of average and peak load electricity from hydropower

• Efficiency η ≈ 85 %

• Medium- or high-pressure plant (medium or high head)

• Two types of dams

• Concrete dam

• Earth-/rockfill dam

• Francis-turbines (medium or high head), Pelton-turbines (high head)

Hydro power plant

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• Pumped storage plants

• Efficiency η ≈ 75 % (storage of base load energy)

• Often combined with storage plants (pumped-storage plants with natural inflow)

• Medium- or high-pressure plant (medium or high head)

• Two types of dams

• Concrete dam

• Earth-/rockfill dam

• Francis-turbines (medium or high head), Pelton-turbines (high head), combined with pumps

Hydro power plant

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• Greenhouse gas emissions during the operation of run-of-river, storage and pumped-storage plants

• As a result of degradation of biomass in the dammed water depending on

• Climatic boundary conditions

• Climatic cold and moderate regions: Increasing CO2-emissions from aerobic degradation of biomass in the first years of operation, then temporary decreasing within the first 10 years of operation

• Climatic tropical regions: Increasing CH4-emissions from anaerobic degradation of biomass in the first years then slower temporary decreasing, which can be longer than the first 10 years of operation

• Vegetal boundary conditions (amount of inundated biomass)

• Sub polar lea, Cultivated land, Steppe, Boreal forest, Rain forest

• Used values of emissions are arithmetic mean values over 100 years of operation and are based on gross greenhouse gas emissions (problem of absorbed CO2 from atmosphere), net emissions are estimated to be 30 – 50 % lower

• Greenhouse gas emissions of run-of-river plants are minimal since the water is not stored for a long time

Hydro power plant

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• Input options of the hydro power LCA-models

• Country-specific distribution of electricity production by hydropower [%]

• Country-specific relation between consumed electricity and generated electricity by pumped-

• storage [kWh/kWh]

• Country-specific greenhouse gas emissions from operation [kg CO2 eq. / kWh]

• Plant-specific efficiency [%]

• Country-specific plant life span and life spans of components [a]

• Country-specific share of concrete dams as a part of storage and pumped storage plants [%]

Wind power plant

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• Data Source: Vestas EPD, 2006 for 1,65 MW turbine.

• Wind Park with 182 turbines including infrastructure (cables, transformer station)

• Manufacturing considered main components (Foundation, Tower, Nacelle Rotor), transports included

• Use phase: full load hours determined by Power produced from wind from IEA statistics divided by installed capacity from World Wind report

• Maintenance considered according to Vestas data

• End-of-Life: recycling potential for metals, incineration of polymers, foundation not recycled, inert materials to landfill

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Agenda

Electricity consumption mix – GaBi screenshot

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Imports

Product output

Parameterized

mixing

process

Energy carrier

supply and

processing

Auxiliary

materials

Power plants

Modelling of electricity consumption mixes

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Used data - basis for all electricity mixes

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• Energy mix, net losses, imports (annual average)

• International Energy Agency (IEA), Electricity Information, Paris, France

• International Energy Agency (IEA), Energy Statistics of Non-OECD Countries, Paris, France

• International Energy Agency (IEA), Energy Balances of Non-OECD Countries, Paris, France

• Eurostat: Eurostat Energy Statistics – imports (by country of origin) – electricity – annual data

• Infrastructure

• FFE München: Ganzheitliche energetische Bilanzierung

energy modelling in gabi 2018 edition€¢input options of the hydro power lca ......

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