comparing centralised and distributed energy storage ... · the thesis aims to produce three sets...

MURDOCH UNIVERSITY

Comparing Centralised and Distributed Energy Storage Options on the Yalgoo (WA) Off-grid Electricity Network to Support High Solar PV

Penetration ENG470 – Engineering Honours Thesis

Written by: Kevin Liang

Unit Coordinator: Professor Parisa Arabzadeh Bahri

Thesis Supervisors: Dr GM Shafiullah & Adjunct Professor Craig Carter

Thesis submitted to the School of Engineering and Information Technology, Murdoch University, in completion of ENG470 Engineering Honours Thesis.

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Abstract

The advancement of the battery energy storage systems (BESS) will maximise the potential of the

renewable hybrid system in the electricity network, and hence create savings for both the electricity

providers and the consumers. The comparison of a centralised BESS and a distributed BESS with

the provision of high solar penetration remains unknown, and the impacts of these hybrid systems

cause on an off-grid diesel network are still uncertain.

The thesis aims to produce three sets of energy flow models with the integration of the rooftop

solar system into Yalgoo, Western Australia, electricity network to identify the reduction of fuel

consumption and the influence on the diesel generators. The energy flow models are Model A –

Diesel only, Model B – Centralised BESS and Model C – Distributed BESS. In addition to that, the

battery system will maintain a 50% state of charge for spinning reserve purposes.

Model A represents the base useage of the existing diesel network in Yalgoo for comparison

purposes, where the required diesel generation equals the load. As for Model B, it uses the rooftop

solar generation for load coverage, and the centralised BESS to accumulate the electrical energy

from either excess solar output or additional generation from diesel to prevent under loading. The

stored energy is then used to reduce diesel loading but not to the extent of under loading. Lastly, for

Model C, the load draws its primary power from the solar system, backup secondarily by the existing

diesel, while the distributed batteries will only be charged with the excess solar generation. Unlike

Model B, distributed batteries only discharge during peak electricity hours when it is the most

expensive.

The final results show that both BESS models reduced the fuel consumptions by roughly 20% with

Model B using slightly more fuel than Model C. However, Model B took the lead for having the

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ability to allow diesel off-mode by using the centralised battery as a virtual diesel. The advantage

leads to no diesel under loading as compared to 561 hours in Model A and 2731 hours in Model C.

Furthermore, the multi-functional centralised BESS offers more benefits than the other systems,

such as black start and voltage control. In summary, Model B – Centralised BESS is the optimal

system for Yalgoo power network.

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Declaration

I, Kevin Liang Xinde, declare that this report comprises no material which has been acknowledged

for the award of any other diploma or degree in my name, in any university or institution and, to the

best of my knowledge and belief, holds no content previously published by another individual,

except where due reference has been made in the text.

Additionally, I verify that no part of this work will, in the future, be used in a submission in my

name, for any other degree or diploma in any university or other tertiary institution without the prior

approval of the Murdoch University. I give consent to this copy of my thesis, when deposited in the

University Library, being made available for loan and photocopying, subject to the provisions of the

Copyright Act 1968. I also give permission for the digital version of my thesis to be made available

on the web, via the University’s digital research repository, the Library Search and also through web

search engines, unless permission has been granted by the University to restrict access for a period

of time.

Name :…………………………………………………..

Signed :…………………………………………………..

Date :…………………………………………………..

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Acknowledgments

Firstly, I would like to express my deepest gratitude to my supervisors, Dr GM Shafiullah and

Adjunct Professor Craig Carter for their continuous support over the duration of the project. Their

guidance enables me to complete the research and writing of this thesis. Beside my supervisors, I

would like to specifically thank Dr Martina Calais for her enthusiasm in teaching and assistance

throughout my studies.

Subsequently, I would like to give my utmost sincere gratitude to Horizon Power, particularly Pierce

Trinkl and Kelli Friar, and Contract Power for providing vital information for the project.

I also thank my family for the unceasing encouragement, support and attention. Without them, I

would not be able to complete my degree in Australia.

I am also grateful to my dearest friends, Nina Lamplough, Natalia Bigaj, Sherwin Chin, Lim Shun

Hong, Tan Hui Kai and Rebecca Soh, for listening, offering me advice and supporting me for my

entire university life. To my manager at work, Carl Johnson, thanks for your understanding of my

tight schedule at university and covering my back when I get into trouble. Special thanks to the CSE

Shenanigans, Sang Ik Park, Didier Alanoix, Blake Weston, Andrew Robinson, Yeshan Yatawara and

Fernando Gonzalaz for the countless drinking sessions. To my university mates, thanks for those

late night studies, coffee sessions, joy and laughter.

Last but not the least, the unit coordinator, Professor Parisa Arabzadeh Bahri, and the staffs for

making this thesis possible.

You.Only.Live.Once.

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Table of Contents

Abstract ...................................................................................................................................... i

Declaration .............................................................................................................................. iii

Acknowledgments ..................................................................................................................... v

Table of Contents .................................................................................................................... vii

List of Figures ....................................................................................................................... xiii

List of Tables ........................................................................................................................... xv

List of Equations ................................................................................................................... xvii

Glossary .................................................................................................................................. xix

Chapter 1 Introduction .............................................................................................................. 1

1.1 Project Objectives ................................................................................................................. 2

Chapter 2 Background .............................................................................................................. 3

2.1 Location – Yalgoo ................................................................................................................. 3

2.1.1 Load Profile ................................................................................................................................................................... 5

2.1.2 Hosting Capacity .......................................................................................................................................................... 7

2.2 Solar Radiation ..................................................................................................................... 9

2.2.1 Hourly Global Solar Radiation on Horizontal Surface - HOMER ................................................................... 11

2.2.2 Declination Angle ....................................................................................................................................................... 12

2.2.3 Solar Time .................................................................................................................................................................... 14

2.2.4 Hour Angle .................................................................................................................................................................. 16

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2.2.5 Incidence Angle .......................................................................................................................................................... 17

2.2.5.1 Horizontal Surface .......................................................................................................................................... 17

2.2.5.2 Tilted Surface ................................................................................................................................................... 18

2.2.6 Hourly Solar Radiation on a Horizontal Surface .................................................................................................. 19

2.2.6.1 Hourly Diffuse Solar Radiation on Horizontal Surface ........................................................................... 20

2.2.6.2 Hourly Direct Beam Solar Radiation on Horizontal Surface .................................................................. 22

2.2.6.3 Ratio of Diffuse Radiation to Direct Beam Radiation ............................................................................. 23

2.2.7 Hourly Solar Radiation on a Tilted Surface ........................................................................................................... 24

2.2.7.1 Hourly Diffuse Solar Radiation on Tilted Surface .................................................................................... 24

2.2.7.2 Hourly Direct Beam Solar Radiation on Tilted Surface ........................................................................... 25

2.2.7.3 Hourly Reflected Solar Radiation on a Tilted Surface .............................................................................. 26

2.3 Battery ........................................................................................................................................ 28

2.3.1 Centralised BESS ....................................................................................................................................................... 29

2.3.2 Distributed BESS ....................................................................................................................................................... 30

2.4 Diesel ................................................................................................................................... 31

2.4.1 Fuel Consumption ..................................................................................................................................................... 32

Chapter 3 Methodology .......................................................................................................... 35

3.1 Energy Flow Models ........................................................................................................... 35

3.1.1 Assumptions ............................................................................................................................................................... 36

3.1.1.1 Load Demand .................................................................................................................................................. 36

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3.1.1.2 Solar Generation .............................................................................................................................................. 37

3.1.1.3 Battery Storage ................................................................................................................................................. 39

3.1.1.4 Diesel ................................................................................................................................................................. 40

3.1.2 Constraints ................................................................................................................................................................... 41

3.1.2.1 Load Demand .................................................................................................................................................. 41

3.1.2.2 Solar Generation .............................................................................................................................................. 41

3.1.2.3 Battery Storage ................................................................................................................................................. 41

3.1.2.4 Diesel Generation............................................................................................................................................ 41

3.2 Model A – Diesel only .......................................................................................................... 42

3.2.1 Diesel Characteristics ................................................................................................................................................. 42

3.3 Model B – Centralised BESS ............................................................................................... 44

3.3.1 Solar Characteristics ................................................................................................................................................... 45

3.3.2 Battery Characteristics ............................................................................................................................................... 46

3.3.2.1 Battery Export to Reduce Diesel Loading .................................................................................................. 47

3.3.2.2 Battery Import to Increase Diesel Loading ................................................................................................ 48

3.3.2.3 Battery Import from Excess Solar................................................................................................................ 49

3.3.2.4 State of Charge at Start of Hour ................................................................................................................... 49

3.3.3 Diesel Characteristics ................................................................................................................................................. 50

3.3.3.1 Diesel Output with Load Fluctuation .......................................................................................................... 50

3.3.3.2 Diesel Output with Solar and Battery Import/Export ............................................................................. 51

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3.4 Model C – Distributed BESS ............................................................................................... 52

3.4.1 Solar Characteristics ................................................................................................................................................... 53

3.4.2 Battery Characteristics ............................................................................................................................................... 53

3.4.2.1 Battery Export during Peak Electricity Charge ......................................................................................... 53

3.4.2.2 Battery Import from Excess Solar ............................................................................................................... 54

3.4.2.3 State of Charge at Start of Hour................................................................................................................... 54

3.4.3 Diesel Characteristics ................................................................................................................................................ 55

3.4.3.1 Diesel Output with Load Fluctuation ......................................................................................................... 55

3.4.3.2 Diesel Output with Solar and Battery Export ........................................................................................... 55

Chapter 4 Results & Discussions ........................................................................................... 57

4.1 Solar Radiation .................................................................................................................... 57

4.1.1 Solar Radiation on Horizontal Surface ................................................................................................................... 57

4.1.1.1 Solar Data from HOMER ............................................................................................................................. 57

4.1.1.2 Solar Radiation with Low Clearness Index ................................................................................................. 58

4.1.1.3 Solar Radiation with High Clearness Index ................................................................................................ 59

4.1.2 Solar Radiation on Tilted Surface ............................................................................................................................ 60

4.1.2.1 Solar Radiation of Various Orientations during Summer ........................................................................ 60

4.1.2.2 Solar Radiation of Various Orientations during Winter .......................................................................... 61

4.1.3 Solar Generation ........................................................................................................................................................ 62

4.2 Battery ................................................................................................................................. 63

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4.2.1 Model B – Centralised BESS .................................................................................................................................... 63

4.2.2 Model C – Distributed BESS ................................................................................................................................... 64

4.3 Diesel ................................................................................................................................... 65

Chapter 5 Conclusion .............................................................................................................. 67

5.1 Summary .............................................................................................................................. 67

5.2 Future Work ......................................................................................................................... 68

Chapter 6 Bibliography ........................................................................................................... 69

Chapter 7 Appendices ............................................................................................................. 75

7.1 Datasheets ........................................................................................................................... 75

7.1.1 Diesel Generator – Cummins QLS9-G5 ............................................................................................................... 75

7.1.2 Solar Panel - LDK 250 PA ....................................................................................................................................... 77

7.2 Solar Radiation .................................................................................................................... 78

7.2.1 Day 5 – Solar Data ..................................................................................................................................................... 78

7.2.2 Day 9 – Solar Data ..................................................................................................................................................... 79

7.2.3 Day 9 – Tilted Surface ............................................................................................................................................... 80

7.2.4 Day 190 – Tilted Surface ........................................................................................................................................... 81

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List of Figures

Figure 2.1: Yalgoo - Average Hourly Load Profile ....................................................................................... 6

Figure 2.2: Hosting Capacity [8] ...................................................................................................................... 7

Figure 2.3: Total Solar Radiation on Tilted Surface [10] .............................................................................. 9

Figure 2.4: Hourly Global Solar Radiation on Horizontal Surface - HOMER ..................................... 11

Figure 2.5: Declination Angle [16] ................................................................................................................ 12

Figure 2.6: Minimum and Maximum Declination Angle [16] [17] .......................................................... 12

Figure 2.7: Equation of Time [20] ................................................................................................................ 14

Figure 2.8: Hour Angle [25] ........................................................................................................................... 16

Figure 2.9: Incidence Angle [26] ................................................................................................................... 17

Figure 2.10: Solar Radiation on a Horizontal Surface [10] ....................................................................... 19

Figure 2.11: Solar Radiation in an Overcast Sky [10]................................................................................. 23

Figure 2.12: Solar Radiation in a Clear Sky [10] ......................................................................................... 23

Figure 2.13: Battery - Lithium-ion [36] ........................................................................................................ 28

Figure 2.14: Schematic Diagram - Centralised BESS [38]......................................................................... 29

Figure 2.15: Schematic Diagram - Distributed BESS [38] ........................................................................ 30

Figure 2.16: Cummins QLS9-G5 - Fuel Consumption ............................................................................. 32

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Figure 2.17: Cummins QSL9-G5 - Efficiency ............................................................................................ 33

Figure 3.1: Model A - Schematic Diagram .................................................................................................. 42

Figure 3.2: Model B - Schematic Diagram .................................................................................................. 44

Figure 3.3: Model C - Schematic Diagram .................................................................................................. 52

Figure 4.1: Solar Radiation on Horizontal Surface (Day 5) ...................................................................... 58

Figure 4.2: Solar Radiation on Horizontal Surface (Day 9) ...................................................................... 59

Figure 4.3: Solar Radiation – Summer (Day 9) ........................................................................................... 60

Figure 4.4: Solar Radiation – Winter (Day 190) ......................................................................................... 61

Figure 7.1: Diesel Output [45] ....................................................................................................................... 75

Figure 7.2: Diesel Specifications [45] ........................................................................................................... 75

Figure 7.3: Diesel Dimensions and Fuel Consumption [45]..................................................................... 76

Figure 7.4: PV Panel Specifications [47] ...................................................................................................... 77

Figure 7.5: PV Panel Mechanical Characteristics [47] ............................................................................... 77

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List of Tables

Table 2.1: Choice of Location - Horizon Power [4] ..................................................................................... 3

Table 2.2: Yalgoo – Weather [7] ...................................................................................................................... 4

Table 2.3: Yalgoo – Average Monthly Load Profile ..................................................................................... 5

Table 2.4: Yalgoo – Hosting Capacity [9] ....................................................................................................... 8

Table 2.5: Ground Albedo of Various Surfaces [35] ................................................................................. 26

Table 2.6: Fuel Consumption - Cummins QLS9-G5 [45] ........................................................................ 32

Table 4.1: Total Global Solar Radiation – HOMER ................................................................................. 57

Table 4.2: Solar Generation of Various Orientations ................................................................................ 62

Table 4.3: Solar Energy Flow ........................................................................................................................ 62

Table 4.4: Centralised BESS - Battery Energy Flow .................................................................................. 63

Table 4.5: Battery Energy Flow of Various Battery Size ........................................................................... 63

Table 4.6: Distributed BESS - Battery Energy Flow ................................................................................. 64

Table 4.7: Diesel Energy Flow ...................................................................................................................... 65

Table 7.1: Solar Data for Day 5 - Overcast Sky ......................................................................................... 78

Table 7.2: Solar Data for Day 9 - Clear Sky ................................................................................................ 79

Table 7.3: Solar Radiation of Various Orientations (Day 9) ..................................................................... 80

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Table 7.4: Solar Radiation of Various Orientations (Day 190) ................................................................ 81

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List of Equations

Equation 2.1 ..................................................................................................................................................... 13

Equation 2.2 ..................................................................................................................................................... 14

Equation 2.3 ..................................................................................................................................................... 15

Equation 2.4 ..................................................................................................................................................... 15

Equation 2.5 ..................................................................................................................................................... 15

Equation 2.6 ..................................................................................................................................................... 16

Equation 2.7 ..................................................................................................................................................... 17

Equation 2.8 ..................................................................................................................................................... 18

Equation 2.9 ..................................................................................................................................................... 19

Equation 2.10 .................................................................................................................................................. 20

Equation 2.11 .................................................................................................................................................. 21

Equation 2.12 .................................................................................................................................................. 21

Equation 2.13 .................................................................................................................................................. 22

Equation 2.14 .................................................................................................................................................. 22

Equation 2.15 .................................................................................................................................................. 24

Equation 2.16 .................................................................................................................................................. 25

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Equation 2.17 ................................................................................................................................................... 25

Equation 2.18 ................................................................................................................................................... 25

Equation 2.19 ................................................................................................................................................... 26

Equation 2.20 ................................................................................................................................................... 32

Equation 2.21 ................................................................................................................................................... 33

Equation 3.1 ..................................................................................................................................................... 42

Equation 3.2 ..................................................................................................................................................... 42

Equation 3.3 ..................................................................................................................................................... 43

Equation 3.4 ..................................................................................................................................................... 45

Equation 3.5 ..................................................................................................................................................... 49

Equation 3.6 ..................................................................................................................................................... 49

Equation 3.7 ..................................................................................................................................................... 54

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Glossary

ARENA Australian Renewable Energy Agency

BESS Battery energy storage system(s)

BOM Bureau of Meteorology

CBD Central business district

DVD Digital versatile disc

kW Kilowatt

kWh Kilowatt-hour

MHC Managed hosting capacity

MW Megawatt

MWh Megawatt-hour

PV Photovoltaics

SOC State of Charge

THC Total hosting capacity

UHC Unmanaged hosting capacity

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Chapter 1 Introduction

In 2015, the Australian Renewable Energy Agency (ARENA) proclaimed that Synergy, Western

Australia largest electricity supplier, will be funding a trial of roof mounted solar systems with

battery storage in Alkimos Beach, Western Australia. [1] A trial that is worth more than $3.3 million

consists of over 100 residential roof mounted photovoltaics (PV) panels and 1.1 MWh of centralised

battery energy storage. The proposal aimed to maximise the potential of this hybrid combination to

reduce grid connection cost, and hence provide savings for both consumers and suppliers.

A year later, a property group named Glenvill proposed to transform YarraBend, a suburb on the

edge of the Melbourne CBD, into world’s first “Tesla town”. [2] The project designed to implement

roof mounted PV systems along with Tesla battery energy storage, Powerwall in all new homes in

the suburb.

Furthermore, the city council of Nedlands, a suburb of Perth, makes it mandatory for new houses to

install a minimum of 1.5 kW renewable systems. [3] As Australia slowly moves towards renewable

resources and battery energy storage systems (BESS), it raises a question whether a centralised BESS

or a distributed BESS is a better option and how these systems impact the existing power network,

especially in a remote community.

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1.1 Project Objectives

The key objectives of the project are to

1. Implement rooftop solar generation with two types of battery energy storage system (BESS),

namely centralised and distributed, into an existing diesel network in an off-grid community,

and

2. Create energy flow models to compare the impact and differences of each system and the

diesel network based on the fuel consumption and diesel loading influence.

Several sub-objectives were implemented for the creation of the energy flow models:

1. Selection of location

2. Data collection of selected location

Load profile

Solar radiation

Diesel details

3. Setup assumptions and constraints for each component

4. Calculate the solar generated electrical output

5. Develop the battery characteristic of both systems

6. Evaluate the required diesel loading and fuel consumption with the implementation of solar

and battery systems.

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Chapter 2 Background

2.1 Location – Yalgoo

For this project, Horizon Power was willing to provide the load profile of any town that is within

their operation. Yalgoo was chosen from the list of locations in Table 2.1, to analyse the difference

between centralised BESS and distributed BESS. High load capacity and high voltage network

system will add unnecessary complexity such as voltage regulation. Therefore, Yalgoo was selected

due to its low load capacity and medium voltage transmission network.

Table 2.1: Choice of Location - Horizon Power [4]

Location Owner Fuel Type 2014 Rated Capacity (MW)

Kalumburu Horizon Power Diesel 1

Kununurra Horizon Power Diesel 10

Onslow Temporary Generation Horizon Power Diesel 3

Yalgoo Horizon Power Diesel 0.4

Yungngora Horizon Power Diesel 0.7

Yalgoo, Western Australia, is an Aboriginal town located 499 kilometres north-east of Perth at

28.3445 °S and 116.6851 °E. [5] The sheep farming town used to be a gold mining town in the early

1890s when gold was first discovered. [6] Table 2.2 (next page) shows that Yalgoo has a desert

climate with scorching summers and cool winters. The town has an average high temperature of

27.9 °C and an average low temperature of 13.2 °C. The average number of precipitation days is only

48.6 days, which is 13.3% of the year, shows that it is an excellent location for solar generation.

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Table 2.2: Yalgoo – Weather [7]

Month Average high (°C) Average low (°C) Average precipitation

(mm) Average precipitation

days

Jan 37.2 20.7 15.8 2.5

Feb 36.3 20.7 25.1 2.9

Mar 33.5 18.6 25.2 3.1

Apr 28.5 14.5 20.8 3.1

May 23.0 10.1 31.3 5.2

Jun 19.2 7.7 41.5 8.0

Jul 18.2 6.2 35.2 7.8

Aug 20.0 6.8 24.7 6.3

Sep 24.0 8.7 11.7 3.6

Oct 27.5 11.4 8.2 2.5

Nov 32.1 15.2 8.0 1.8

Dec 35.5 18.4 11.1 1.8

Year 27.9 13.2 260.8 48.6

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2.1.1 Load Profile

According to the hourly load profile provided by Horizon Power, the annual energy consumption of

Yalgoo is 996.1 MWh, and the average load demand, peak load demand and minimum load demand

of each month were provided as shown in Table 2.3.

Table 2.3: Yalgoo – Average Monthly Load Profile

Month Average Load (kW) Peak Load (kW) Minimum Load (kW)

Jan 147.0 284.6 61.6

Feb 150.1 280.3 58.0

Mar 129.4 256.5 51.6

Apr 99.9 239.4 20.5

May 89.3 186.9 25.2

Jun 108.9 215.5 52.4

Jul 113.4 218.2 41.2

Aug 99.5 197.6 37.4

Sep 92.3 172.5 51.5

Oct 90.2 188.9 45.6

Nov 117.4 216.1 42.5

Dec 129.5 226.5 63.9

Annual 113.7 284.6 20.5

The load of Yalgoo varied immensely throughout the year with an annual average of 113.7 kW. The

highest peak load can be found in January at 284.6 kW, and there was an enormous 223 kW

difference between the peak and minimum load. The lowest load can be accessed during autumn in

April at 20.5 kW. Summer and winter have a relatively higher average load compared to spring and

autumn, and this may be due to the usage of the air conditioner during summer and heating during

winter.

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Figure 2.1: Yalgoo - Average Hourly Load Profile

Figure 2.1 is the average hourly load profile generated using the annual hourly data given by Horizon

Power. It shows that Yalgoo has a very typical residential load profile, where the lowest average load

can be seen in the early hours at 4am, and slowly increase towards the 100 kW mark by 8am, as the

residents are off to work or school. The average load stays around the 110 kW to 130 kW regions

from 8am to 5pm. As people head home for the day, the average load increased significantly till it

reached the peak around 7pm and 8pm. After 8pm, it gradually reduced to the minimum average

load in the morning.

0

20

40

60

80

100

120

140

160

180

0 5 10 15 20

Lo

ad

(k

W)

Hour of day

Yalgoo - Average Hourly Load Profile

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2.1.2 Hosting Capacity

Horizon Power only permits a limited amount of consumer owned renewable systems connected to

their systems. This limit is acknowledged as hosting capacity, and it is set at a level that assists

Horizon Power to provide a reliable electricity supply. [8]

Figure 2.2: Hosting Capacity [8]

Hosting capacity is categorised into two segments, unmanaged and managed. Figure 2.2 shows the

method used for the constraint of renewable system, starting with a limited unmanaged hosting

capacity (UHC). UHC is for residential consumers who want to install a renewable system of not

more than five kilowatts [9]. The amount of UHC allowed depends on the loading of the diesel

generator, and too much UHC will cause undesired diesel under loading, which is harmful to the

diesel generator lifespan over an extended period of time. The total hosting capacity can be

increased with the combination of generation management systems, known as managed hosting

capacity (MHC). Generation management systems control and managed the renewable source

electricity such as a battery energy storage system, BESS. Total

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Table 2.4: Yalgoo – Hosting Capacity [9]

Town Unmanaged hosting

capacity (kW) Managed hosting capacity

(kW) Total hosting capacity

(kW)

Yalgoo 0 164 164

According to Horizon Power, Yalgoo has a hosting capacity of 164 kW as displayed in Table 2.4. [9]

Low load profile in the early hours may be the reason why the hosting capacity is limited to only

managed hosting capacity (Refer to 2.1.1 Load Profile), as additional unmanaged renewable systems

may cause undesired diesel under loading situation.

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2.2 Solar Radiation

Figure 2.3: Total Solar Radiation on Tilted Surface [10]

Total solar radiation consists of three parts, direct beam solar radiation, diffused solar radiation and

reflected solar radiation. Direct beam solar radiation refers to the electromagnetic radiation that

travels directly from the Sun to the PV panels as shown in Figure 2.3. Diffuse solar radiation is the

electromagnetic radiation that falls onto the PV panels after been dispersed by particles from the

atmosphere. Reflected solar radiation describes the radiation that has being reflected from the

ground, also known as the Albedo effect. Reflected solar radiation does not apply on PV panels on a

horizontal surface, as the panels sit on the same plane as the ground. [11]

Total solar radiation varies throughout the day, and that determines the solar flow characteristic of

the energy models. Furthermore, houses in Yalgoo were not built to have roof space for north

facing solar panels and roof pitch angle should also be taken into consideration. Therefore, the

minimum requirement is to have hourly solar data of various orientations with a tilt angle of

22.5 °[12], which is the typical roof pitch angle in Australia. The most accurate solar data comes

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from the Bureau of Meteorology (BOM) as it has a weather station located within 50km of Yalgoo

[13], but unfortunately, there is a huge price tag to purchase this data.

Alternately, the hourly solar radiation on a horizontal surface can be acquired using the HOMER

simulator. Then by reverse engineering the equation used for hourly solar radiation on the

horizontal surface, along with basic of declination angle, solar time, hour angle and incidence angle,

the position of the sun can be anticipated. Lastly, by adding in the tilt angle and azimuth of the panel,

the hourly solar radiation on a tilted angle can then be converted.

Steps to calculate hourly solar radiation on a tilted surface:

1. Hourly global solar radiation using the HOMER simulator

2. Declination angle

3. Solar time

4. Hour angle

5. Incidence angle

- Horizontal surface

- Tilted surface

6. Hourly solar radiation on horizontal surface

- Hourly diffuse solar radiation

- Hourly direct-beam solar radiation

7. Hourly solar radiation on tilted surface

- Hourly diffuse solar radiation

- Hourly direct-beam solar radiation

- Hourly reflected solar radiation

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2.2.1 Hourly Global Solar Radiation on Horizontal Surface - HOMER

HOMER, developed by the National Renewable Energy Laboratory [14], is a free simulator that can

be used to design and analyse technical and financial aspects for remote, stand-alone and distributed

generation applications in both off-grid and on-grid power networks.

Figure 2.4: Hourly Global Solar Radiation on Horizontal Surface - HOMER

A dummy simulation was created in the HOMER to obtain the hourly global solar radiations on a

horizontal surface in Yalgoo as shown in Figure 2.4. This data, originally from the NASA database

[15], was then exported as a ‘.csv’ file for energy flow model simulation using Microsoft Excel.

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2.2.2 Declination Angle

Figure 2.5: Declination Angle [16]

Declination angle is the angle between the Earth’s celestial equator and the line of the Sun as shown

in Figure 2.5. The earth’s obliquity causes the declination angle to vary from -23.45° to +23.45°.

Figure 2.6: Minimum and Maximum Declination Angle [16] [17]

Figure 2.6 indicates that -23.45° happens around 21st December when the northern part of the earth

tilts away from the Sun, and around 21st June, the southern part of the earth tilts away to form the

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positive 23.45°. During the spring and autumn equinoxes, 21st March and 21st September, the Sun

passes directly over the Earth’s celestial equator. [18]

Declination angle, δ [19] (in degrees)

𝛿 = 23.45 × sin [360

365(284 + 𝑛)] Equation 2.1

Where,

n is the day number in a year (1st of January is day 1 and 1st of June is day 152)

Note: The equation is based on the assumption that it is not a leap year.

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2.2.3 Solar Time

Figure 2.7: Equation of Time [20]

Solar time is the calculation of time relative to the Sun’s position in the sky. The length of solar day

changes over the year due to two main reasons. The Earth’s orbit around the Sun is an ellipse, and

therefore it moves quicker when it is nearest to the Sun, and slower when it is furthest. Another

reason is that of the Earth’s obliquity, the motion around the Sun is tilted to the Earth’s celestial

equator (Refer to 2.2.2 Declination Angle). [21] [22] Thus, the equation of time was created, and as

shown in Figure 2.7, time varies throughout the year.

Solar time, 𝑡𝑠 [19] [23] (in decimal hours in a day)

𝑡𝑠 = 𝑡𝑐 +4(𝐿𝑙𝑜𝑐 − 𝐿𝑠𝑡)

1440+

𝐸𝑜𝑡

1440 Equation 2.2

Where,

𝑡𝑐 is the standard civil time in hours

𝐿𝑙𝑜𝑐 is the longitude of the location in degrees

𝐿𝑠𝑡 is the standard meridian for the local time zone in degrees (Refer to Equation 2.3)

Eot is the equation of time in degrees (Refer to Equation 2.4)

15 | P a g e

Note: Part of the equations was divided by 1440 to convert degrees to minutes.

Standard meridian for the local time zone, 𝐿𝑠𝑡 [24] (in decimal hours in a day)

𝐿𝑠𝑡 = 𝐺𝑀𝑇 × (360°

24 ℎ𝑜𝑢𝑟𝑠) Equation 2.3

Where,

GMT is the Greenwich Mean Time of the location in decimal hours in a day

Equation of time, Eot [19] (in decimal hours in a day)

𝐸𝑜𝑡 = 229.2(0.00075 + 0.001868 cos 𝐵 − 0.032077 sin 𝐵− 0.014615 cos 2𝐵 − 0.04089 sin 2𝐵)

Equation 2.4

With parameter B

𝐵 = (𝑛 − 1) (360

365) Equation 2.5

Where,

n is the day number in a year (1st of January is day 1 and 1st of June is day 152)

Note: Daylight saving has been neglected in the equation as it does not apply to the location of

research.

16 | P a g e

2.2.4 Hour Angle

Figure 2.8: Hour Angle [25]

Hour angle transforms the solar time (Refer to 2.2.3 Solar Time) into the degrees which the Sun

travels across the sky as displayed in Figure 2.8. Each solar hour represents 15 degrees angular

motion of the Sun with solar noon as 0°, negative hour angle in the morning and positive hour angle

after solar noon. [24]

Hour angle, ω [19] [23]

𝜔 = (𝑡𝑠 −12 ℎ𝑜𝑢𝑟𝑠

24 ℎ𝑜𝑢𝑟𝑠) × 24 ℎ𝑜𝑢𝑟𝑠 × 15° Equation 2.6

Where,

𝑡𝑠 is the solar time (Refer to Equation 2.2)

17 | P a g e

2.2.5 Incidence Angle

Figure 2.9: Incidence Angle [26]

Incidence angle refers to the angle between the direction of sunlight and the perpendicular to the

surface as shown in Figure 2.9. [27] Angles of incidence greater than 90° are clipped to zero as the

Sun is behind the panel.

2.2.5.1 Horizontal Surface

Incidence angle on horizontal surface, θz [19] (in degrees)

𝜃𝑧 = cos−1[(sin 𝛿 sin ∅) + (cos 𝛿 cos ∅ cos 𝜔)] Equation 2.7

Where,

δ is the declination angle (Refer to Equation 2.1)

∅ is the latitude of the location (Refer to 3.1 Location – Yalgoo)

ω is the hour angle (Refer to Equation 2.6)

Note: Equation 2.7 and Equation 2.8 are identical except that the tilt angle for a horizontal surface

is 0 ° and the azimuth does not change, and hence part of the equation was voided.

18 | P a g e

2.2.5.2 Tilted Surface

Incidence angle on a tilted surface, θ [19] (in degrees)

𝜃 = cos−1[(sin 𝛿 sin ∅ cos 𝛽) − (sin 𝛿 cos ∅ sin 𝛽 cos 𝛾)+ (cos 𝛿 cos ∅ cos 𝛽 cos 𝜔) + (cos 𝛿 sin ∅ sin 𝛽 cos 𝛾 cos 𝜔)+ (cos 𝛿 sin 𝛽 sin 𝛾 sin 𝜔)]

Equation 2.8

Where,



β is the tilt angle of the solar panel (Refer to 3.1.1 Assumptions)

𝛾 is the azimuth angle of the solar panel (180° for a north facing panel and 90° for a west facing panel)

ω is the hour angle (Refer to Equation 2.6)

Note: If the incidence angle for panel on horizontal surface is zero, the incidence angle on a tilted

surface should also be zero because the Sun has not yet risen or has set.

19 | P a g e

2.2.6 Hourly Solar Radiation on a Horizontal Surface

The hourly solar radiation data attained from HOMER simulator (Refer to 3.2.1 Hourly Global

Solar Radiation on Horizontal Surface – HOMER) comprises two main parts, direct beam solar

radiation and diffuse solar radiation, as shown in Figure 2.10. [11]

Figure 2.10: Solar Radiation on a Horizontal Surface [10]

Hourly global solar radiation on horizontal surface, 𝐼𝐻 [28] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝐻 = 𝐼𝑑 + 𝐼𝑏 Equation 2.9

Where,

𝐼𝑑 is the hourly diffused radiation on horizontal surface

𝐼𝑏 is the hourly direct beam solar radiation on horizontal surface

Note: 𝐼𝐻 is the hourly global solar radiation on a horizontal surface obtained from HOMER

simulator (Refer to 3.2.1 Hourly Global Solar Radiation on Horizontal Surface)

20 | P a g e

2.2.6.1 Hourly Diffuse Solar Radiation on Horizontal Surface

The ratio of direct beam solar radiation and diffuse solar radiation has to be determined to convert

the hourly solar radiation on a horizontal surface to hourly solar radiation on a tilted surface. There

are two mathematical models to approximate the diffuse radiation on a horizontal surface, as follows:

Parametric models

Decomposition models

Parametric models require precise atmospheric details to calculate diffuse solar radiation, such as

cloud conditions and atmospheric turbidity. This data is not possible to acquire as there is a

limitation of data available from the HOMER simulator. Alternately, decomposition models use

only global solar radiation to predict the ratio of diffuse radiation in the sky. Decomposition models

are constructed on the relationships between the clearness index and the diffuse fraction [29] and

model chosen for the project is Boland’s model [30]. It was developed using the hourly solar data

from a weather station located at Deakin University, Victoria, and then tested with data from other

locations in Australia.

Extraterrestrial normal radiation, 𝐼𝑜𝑛 [19] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑜𝑛 = 𝐼𝑠𝑐 + (cos (360 × 𝑛

365)) Equation 2.10

Where,

𝐼𝑠𝑐 is the solar constant, 1367 𝑊/𝑚2

𝑛 is the day number in a year (1st of January is day 1 and 1st of June is day 152)

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Hourly extraterrestrial horizontal radiation, 𝐼𝑜 [19] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑜 =12

𝜋𝐼𝑜𝑛 [cos ∅ cos 𝛿 (sin 𝜔2 − sin 𝜔1) +

𝜋(𝜔2 − 𝜔1)

180°sin ∅ sin 𝛿] Equation 2.11

Where,

𝐼𝑜𝑛 is the extraterrestrial normal radiation (Refer to Equation 2.10)



𝜔1 is the hour angle at the start of each time step

𝜔2 is the hour angle at the end of each time step

Note: Due to limited data, the first hour angle (Day 1 – 0000 hours) will be taken as the ending

hour angle of the last day (Day 365 – 2300 hours).

Hourly clearness index, 𝑘𝑡 [19]

𝑘𝑡 =𝐼𝐻

𝐼𝑜 Equation 2.12

𝐼𝐻 is the hourly global solar radiation on horizontal surface (Refer to 3.2.1 Hourly Global Solar

Radiation on Horizontal Surface)

𝐼𝑜 is the hourly extraterrestrial horizontal radiation (Refer to Equation 2.11)

Note: Clearness index is 0 for overcast and 1 for clear sky. [31]

22 | P a g e

Using Boland’s model, the hourly diffuse solar radiation on horizontal surface, 𝐼𝑑 [30] (in 𝑊ℎ/𝑚2

or 𝑘𝑊ℎ/𝑚2)

𝐼𝑑 = (1

1 + 𝑒7.997(𝑘𝑡−0.586)) 𝐼𝐻 Equation 2.13

𝐼𝐻 is the hourly global solar radiation on a horizontal surface (Refer to 3.2.1 Hourly Global

Solar Radiation on Horizontal Surface)

𝑘𝑡 is the hourly clearness index (Refer to Equation 2.12)

2.2.6.2 Hourly Direct Beam Solar Radiation on Horizontal Surface

The hourly direct beam solar radiation can be derived by rearranging Equation 2.9.

Direct beam solar radiation on a horizontal surface, 𝐼𝑏 (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑏 = 𝐼𝐻 − 𝐼𝑑 Equation 2.14

Where,

𝐼𝐻 is the hourly global solar radiation on a horizontal surface (Refer to 3.2.1 Hourly Global

Solar Radiation on Horizontal Surface)

𝐼𝑑 is the hourly diffuse solar radiation on a horizontal surface (Refer to Equation 2.13)

23 | P a g e

2.2.6.3 Ratio of Diffuse Radiation to Direct Beam Radiation

Figure 2.11: Solar Radiation in an Overcast Sky [10]

The clearness Index describes the ratio of solar radiation on a horizontal surface to the

extraterrestrial radiation outside of the atmosphere [31], where a value of 1 represents clear sky and

0 for overcast. On an overcast day, the total solar radiation is low, and the ratio of diffuse radiation

should be higher than direct beam radiation, as shown in Figure 2.11. That is because clouds

scattered most of the Sun's direct beam radiation, and then redirected onto the panel.

Figure 2.12: Solar Radiation in a Clear Sky [10]

In contrast, Figure 2.12 shows that a high clearness index produces a higher ratio of direct beam

radiation to diffuse radiation, due to lesser obstruction along the Sun’s rays.

24 | P a g e

2.2.7 Hourly Solar Radiation on a Tilted Surface

Hourly solar radiation on a tilted surface is comprised of three components, direct beam solar

radiation, diffuse solar radiation and reflected solar radiation as showed in Figure 2.3. [11]

Hourly solar radiation on a tilted surface, 𝐼𝛽 [28] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝛽 = 𝐼𝑑𝛽 + 𝐼𝑏𝛽 + 𝐼𝑟 Equation 2.15

Where,

𝐼𝑑𝛽 is the diffused solar radiation on a tilted surface (Refer to Equation 2.16)

𝐼𝑏𝛽 is the direct beam solar radiation on a tilted surface (Refer to Equation 2.17)

𝐼𝑟 is the reflected solar radiation on a tilted surface (Refer to Equation 2.20)

2.2.7.1 Hourly Diffuse Solar Radiation on Tilted Surface

Diffuse solar radiation model on a tilted surface are categorised into two models, as follows:

Isotropic models

Anisotropic models

Isotropic models assume that the concentration of diffuse solar radiation is uniform over the

atmosphere, while anisotropic models postulate that anisotropic of diffuse solar radiation occurs in

the circumsolar region along with the isotopically dispersed diffuse element. [32] Using Liu and

Jordan’s model (Isotropic model) [32] [33], the diffuse solar can be derived as follows:

25 | P a g e

Hourly diffuse solar radiation on tilted surface, 𝐼𝑑𝛽 [32] [33] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑑𝛽 = (1 + cos 𝛽

2) × 𝐼𝑑 Equation 2.16

Where,

𝛽 is the tilt angle (Refer to 4.1.1 Assumptions)

𝐼𝑑 is the diffuse solar radiation on a horizontal surface (Refer to Equation 2.10)

2.2.7.2 Hourly Direct Beam Solar Radiation on Tilted Surface

Hourly direct beam solar radiation on a tilted surface, 𝐼𝑏𝛽 [34] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑏𝛽 = 𝑟𝑏 × 𝐼𝑏 Equation 2.17

Where,

𝑟𝑏 is the ratio of radiation collected by tilted surface to radiation collected by horizontal surface

(Refer to Equation 2.18)

𝐼𝑏 is the direct beam solar radiation on a horizontal surface (Refer to Equation 2.14)

Ratio of radiation collected by a tilted surface to radiation collected by horizontal surface, 𝑟𝑏

𝑟𝑏 =𝐼𝑜𝛽

𝐼𝑜≈

cos 𝜃

cos 𝜃𝑧 Equation 2.18

Where,

𝜃 is the incidence angle on a tilted surface (Refer to Equation 2.8)

𝜃𝑧 is the incidence angle on a horizontal surface (Refer to Equation 2.7)

26 | P a g e

2.2.7.3 Hourly Reflected Solar Radiation on a Tilted Surface

After the solar radiation reaches the Earth’s surface, the amount of radiation absorbed or reflected is

determined by the albedo of the surface. Albedo is the proportion of radiation reflected off the

ground, and it varies due to the angle of incidence from the Sun. [35] Average values have been

calculated to simplify the calculation of reflected solar radiation on a tilted surface as shown in Table

2.5.

Table 2.5: Ground Albedo of Various Surfaces [35]

Surface Upper limit Lower limit Average

Soil (Dark and wet) 0.05 0.225 0.14

Soil (Light and dry) 0.225 0.4 0.31

Sand 0.15 0.45 0.30

Grass (Long) 0.16 0.21 0.19

Grass (Short) 0.21 0.26 0.24

Agricultural crops 0.18 0.25 0.22

Tundra 0.18 0.25 0.22

Forest (Deciduous) 0.15 0.2 0.18

Forest (Coniferous) 0.05 0.15 0.10

Water 0.03 1 0.52

Snow (Old) 0.4 0.675 0.54

Snow (Fresh) 0.675 0.95 0.81

Ice (Sea) 0.3 0.45 0.38

Ice (Glacier) 0.2 0.4 0.30

Clouds (Thick) 0.6 0.9 0.75

Clouds (Thin) 0.3 0.5 0.40

Hourly reflected solar radiation on tilted surface, 𝐼𝑟 [32] (in 𝑊ℎ/𝑚2 or 𝑘𝑊ℎ/𝑚2)

𝐼𝑟 = 𝐼𝐻 × 𝜌 × (1 − cos 𝛽

2) Equation 2.19

Where,

𝐼𝐻 is the hourly global solar radiation on horizontal surface (Refer to 2.2.1 Hourly Global Solar

Radiation on Horizontal Surface)

27 | P a g e

𝛽 is the tilt angle (Refer to 3.1.1 Assumptions)

𝜌 is the ground albedo (Refer to Table 2.5 and 3.1.1 Assumptions)

28 | P a g e

2.3 Battery

The battery is storage of charge in electrochemical cells that generates a movement of electrons in a

circuit when chemically reacted. It is comprised of three basic components, an anode, cathode and

electrolyte as shown in Figure 2.13.

Figure 2.13: Battery - Lithium-ion [36]

The anode (positive) and cathode (negative) are separated by an electrolyte. When the battery is

connected to a load, a chemical reaction between the anode and electrolyte causes electrons to flow

from the anode through to the circuit and back to the cathode. [37]

29 | P a g e

2.3.1 Centralised BESS

Figure 2.14: Schematic Diagram - Centralised BESS [38]

A centralised BESS refers to a single large electricity storage system in a power network as shown in

Figure 2.14. The centralised BESS is typically connected to the transmission network, and usually

owned and operated by the electricity supplier. It provides numerous functions and advantages in a

power network due to its point of connection, such as: [39]

1. Smoothing over short-term fluctuation

2. Cancelling reactive power

3. Providing voltage control

4. Enabling peak shaving

5. Offering an uninterruptible electricity supply

30 | P a g e

6. Increasing grid stabilisation

7. Providing black start

8. Offering frequency control

2.3.2 Distributed BESS

Figure 2.15: Schematic Diagram - Distributed BESS [38]

A distributed BESS refers to several small battery storage systems installed at the end of the network,

usually near the consumer’s load. The distributed BESS does not have as many functions as the

centralised BESS due to its point of connection, the edge of the low voltage network. It has certain

abilities such as spinning reserve coverage, peak shaving and short-term load fluctuation, but it is

limited to only the participating houses. In addition to that, the distributed BESS, which is usually

owned by the electricity consumers, only has an objective to reduce utility bills, and thus it does not

post an influence on the grid or diesel generators.

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2.4 Diesel

In 2016, a contract was given to Contract Power by Horizon Power Regional Power Corp to supply

electricity for six towns in the Midwest region of Western Australia, and Yalgoo is one of them. [40]

Due to confidentiality, Contract Power only discloses the following details about the agreement:

It operates with three sets of Cummins QSL9 units

The generators have a prime rating of 240 kW

It operates with one generator for the majority of the year

The details lead to Cummins QSL9-G5 with a prime rating of 300 kVA and 240kWe at 1500 rpm.

[41] The six cylinder turbocharged generators were designed and constructed to comply with ISO

8528 and ISO 9001 regulations, with a phase rating of 50 Hz and power factor of 0.8. [42] (Refer to

Appendix)

One generator operation for the majority of the year shows that Contract Power is working with a

zero contingency plan. In the event of diesel tripping, Yalgoo will lose power until the start of a

second generator. Assuming the diesel generator has a minimum loading of 30 percent (Refer to

3.1.1 Assumptions) [43], and by comparing that with the load profile, 561 hours of the year the

diesel generator was running below the minimum diesel loading. Over an extended operating period,

this may cause wet stacking in the diesel generator, where carbon build up in the generator [44] and

result in poor performance and reliability [43].

32 | P a g e

2.4.1 Fuel Consumption

Table 2.6: Fuel Consumption - Cummins QLS9-G5 [45]

Diesel loading Diesel output (x) Fuel consumption (y) Efficiency

% kW L/h kWh/L

25 60 17.0 3.529

50 120 31.0 3.871

75 180 46.0 3.913

100 240 63.0 3.810

Table 2.6 shows the fuel consumption of a Cummins QLS9-G5 diesel generator with a maximum of

63 litres per hour at 100 percent load (Refer to Appendix). The maximum percentage loading

remains unknown due to lack of disclosed information. Hence the base output, 203 kW, was

assumed to be the maximum loading.

Figure 2.16: Cummins QLS9-G5 - Fuel Consumption

17.0

31.0

46.0

63.0

y = 8E-07x3 - 0.0001x2 + 0.2389x + 3

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0 25 50 75 100 125 150 175 200 225 250

Fu

el

co

nsu

mp

tio

n (

L/

h)

Diesel output (kW)

Fuel Consumption

𝐹𝑢𝑒𝑙 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 = 0.0000008𝑥3 − 0.0001𝑥2 + 0.2389𝑥 + 3 Equation 2.20

33 | P a g e

The fuel curve of QLS9-G5 can be derived using the information from Table 2.6, and then a 3rd

order polynomial trendline was added to search for the missing data along the fuel curve as shown

in Equation 2.20 and Figure 2.16. The equation displays a constant of 3, indicates the fuel

consumption at zero/no load is 3 litres per hour.

Figure 2.17: Cummins QSL9-G5 - Efficiency

𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 =𝐷𝑖𝑒𝑠𝑒𝑙𝑜𝑢𝑡𝑝𝑢𝑡

𝐹𝑢𝑒𝑙 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 Equation 2.21

The efficiency of the generator was then calculated and plotted as displayed in Figure 2.17 using

Equation 2.20. It is least efficient at 0% loading and most efficient around 57% to 66% loading at

3.82 kWh per litre. The efficiency stays relatively constant after 30% loading showing the generator

has efficient fuel consumption and that could be the reason why Contract Power choice a larger

generator with zero contingency.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0 10 20 30 40 50 60 70 80 90 100

Fu

el

Eff

icie

ncy

(kW

h/

L)

Diesel loading (%)

Fuel Efficiency

34 | P a g e


35 | P a g e

Chapter 3 Methodology

3.1 Energy Flow Models

Energy flow models provide a feasibility study of both centralised and distributed battery storage in

a community. The models were created using Microsoft Excel to display hourly energy analysis of

each element, such as solar generation, battery state of charge (SOC) and required diesel generation.

An additional model named “diesel only” was constructed to investigate the impact that these

battery setups have on the existing power network in Yalgoo. The following models were created:

1. Model A – Diesel only

Centralised diesel and no storage

- The existing diesel set up at Yalgoo.

2. Model B – Centralised BESS

Distributed solar system

- Distributed roof-mounted photovoltaic systems on residential houses.

Centralised BESS system

- Centralised battery system operated by the electricity supplier that operates

along with existing diesel.

Centralised diesel


3. Model C – Distributed BESS

Distributed photovoltaic system

- Distributed roof-mounted photovoltaic systems on residential houses.

Distributed BESS system

36 | P a g e

- Distributed battery systems in residential houses with a photovoltaic system.

Centralised diesel


Assumptions and constraints were formed for the development of each model, and these

assumptions will establish the characteristic of the battery, the solar and the diesel.

3.1.1 Assumptions

3.1.1.1 Load Demand

Assume:

1. The number of residential houses to be 130.

According to Census, Yalgoo has a population of 405 in 2011 and an average of 3.1

people per household. [46]

2. The load profile obtained by Horizon Power is before solar reduction.

There is a possibility that the load profile has been reduced by the existing solar

systems in Yalgoo, but due to the lack of information, it can only be assumed that

that is the base load profile.

3. Transmission losses were included in the load profile.

4. No load fluctuation for Model A – Diesel only

No solar generation occurs, therefore the load is equals to diesel output.

5. 30% of diesel base rating, 203kW, a 60.4 kW load fluctuation is taken into consideration for

Model B – Centralised BESS

37 | P a g e

If there is a sudden drop in solar generation, the centralised BESS has the ability to

act as a virtual diesel set to handle the load. Therefore, the load fluctuation is

equivalent to a diesel minimum loading.

6. 164 kW load fluctuation for Model C – Distributed BESS

If there is a sudden drop in solar generation, the electricity supplier does not have

the ability to control distributed BESS to provide the electrical energy. Hence the

load fluctuation is equivalent to the hosting capacity.

3.1.1.2 Solar Generation

Assume:

1. Distributed photovoltaic systems are located on the roof of all residential houses.

2. PV panels used were LDK 2650 PA (Refer to Appendix) [47]

Output : 250 Watt

Efficiency : 15.5%

Surface area : 1.613 𝑚2

Mounting : Roof mounted

Tilt angle : 22.5°

Perth has a typical roof pitch of 22.5◦ [12]

3. 52 residential houses with 3 kW solar system and 2 residential houses with 4 kW solar system

Hosting capacity limit of 164 kW can be derived to:

52 ℎ𝑜𝑢𝑠𝑒𝑠 × 12 𝑝𝑎𝑛𝑒𝑙𝑠 × 250 𝑤𝑎𝑡𝑡 𝑝𝑒𝑟 𝑝𝑎𝑛𝑒𝑙 = 156 𝑘𝑊

2 ℎ𝑜𝑢𝑠𝑒𝑠 × 16 𝑝𝑎𝑛𝑒𝑙𝑠 × 250 𝑤𝑎𝑡𝑡 𝑝𝑒𝑟 𝑝𝑎𝑛𝑒𝑙 = 8 𝑘𝑊

𝑇𝑜𝑡𝑎𝑙 = 156 𝑘𝑊 + 8 𝑘𝑊 = 164 𝑘𝑊

4. Orientation of PV panels

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Not all houses in Yalgoo have roof space for north facing panels, and it can only be

assumed that there are 5 different orientations for the panels.

West : 20%

North-west : 20%

North : 20%

North-east : 20%

East : 20%

5. Solar output de-rating factor

The solar generation of PV panels can be reduced by factors such as manufacturing

tolerance, dirt on a panel’s surface and ambient temperature. [48]

Manufacturing tolerance,𝑓𝑚𝑎𝑛 : 3%

Dirt on PV panel, 𝑓𝑑𝑖𝑟𝑡 : 5%

Drop in efficiency due to temperature, 𝑓𝑡𝑒𝑚𝑝 : 17%

- Derating factor can be calculated with the ambient temperature, but

due to the lack of information, it can only be assumed.

6. Inverter efficiency factor

DC electricity generated from the panel will have to go through an inverter for AC

conversion before going to the load or grid. During the conversion the generation

will encounter a few efficiency losses. [48]

DC cable efficiency, 𝑛𝑃𝑉_𝑖𝑛𝑣 : 97%

Inverter efficiency, 𝑛𝑖𝑛𝑣 : 97%

AC cable efficiency, 𝑛𝑖𝑛𝑣_𝑠𝑏 : 99%

7. Electricity generated from solar is the primary source of electricity to cover the load.

8. Surroundings are covered with sand, reflecting 0.3 ground albedo. Refer to Table 2.5:

Ground Albedo of Various Surfaces [35]

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3.1.1.3 Battery Storage

Assume:

1. The battery initial SOC is 50%.

2. The battery size is the same as the hosting capacity, 164 kWh.

Distributed BESS is assumed to have 1:1 solar to battery ratio in the house.

Centralised BESS should have the same amount of battery capacity as distributed

BESS to compare the models.

3. The battery has the characteristic of a lithium-ion.

4. The battery can be fully charged or fully discharged within an hour, 164 kWh.

5. Charge and discharge losses of 5%.

6. Batteries are maintained above 50% SOC for spinning reserve coverage also known as

minimum battery SOC.

7. For Model B – Centralised BESS

The main source of input is from excess solar after covering the load

The secondary source is from diesel, but only if diesel is under loaded.

The battery will discharge to cover the load when:

- The battery can handle the remaining load, after solar reduction, without

going below 50% SOC.

- The diesel loading is above its minimum loading.

8. For Model C – Distributed BESS

Battery only be charged by excess solar after covering the load

- Consumers will not want to pay additional money to charge the battery from

the grid. Hence, it should only be charged using any excess solar energy.

Battery only discharges during peak electricity hours

40 | P a g e

- Consumers will want to reduce usage of grid/diesel during peak hours to

save more money.

3.1.1.4 Diesel

Assume:

1. It is the same as the existing centralised diesel.

2. Maximum diesel loading at 100% is 203 kW.

The maximum diesel loading is assumed to be the maximum base loading of the

generator, due to unknown diesel loading practised by Contract Power or Horizon

Power. (Refer to Appendix 7.1.1)

3. Minimum diesel loading at 30%, 60.9 kW.

The recommended minimum loading by Cummins, makers of the generator. [43]

4. For model A – Diesel only

Minimum number of online diesel sets : 1

Maximum number of online diesel sets : 3

5. For model B - Centralised BESS


- Centralised battery is able to act as virtual diesel


6. For model B - Distributed BESS



7. If the battery is disconnected is below the 50% SOC, diesel should take the load fluctuation

into consideration.

41 | P a g e

3.1.2 Constraints

3.1.2.1 Load Demand

1. The load must not require more than three diesel generators.

3.1.2.2 Solar Generation

1. Total solar radiation does not consist of direct beam solar radiation if the incident angle is

greater than 85 degrees. Reason been incident angle larger than 90 degrees indicates the Sun

is behind the PV panel, and due to the uneven Earth’s surface, a 5 degree error should be

taken into consideration.

2. Solar generation should not be limited or cut off due to diesel loading.

3.1.2.3 Battery Storage

1. Battery coverage should not cause the diesel generator to under load.

2. Spinning reserve to be 50% of battery SOC.

3. Battery energy storage should not discharge by more than 50%.

3.1.2.4 Diesel Generation

1. The diesel generator should not operate above 100% loading.

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3.2 Model A – Diesel only

Figure 3.1: Model A - Schematic Diagram

Model A shown in Figure 3.1, consists of just diesel generators as the source of electricity generation,

and it is to simulate the existing energy system of Yalgoo. The model shows the initial characteristics

of the diesel generator before addition of solar and battery. These characteristics are vital to analyse

the impact Model A and Model B will have on the power network.

3.2.1 Diesel Characteristics

𝐿𝑜𝑎𝑑 = 𝐷𝑖𝑒𝑠𝑒𝑙𝑜𝑢𝑡𝑝𝑢𝑡 Equation 3.1

The conservation of energy, the total energy in an isolated network stays the same. It cannot be

created or removed, but it changes from one form to another and energy in is equal to energy out.

[49] Therefore, the diesel output equals to the load input:

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑜𝑛𝑙𝑖𝑛𝑒 𝑑𝑖𝑒𝑠𝑒𝑙 = 𝑟𝑜𝑢𝑛𝑑𝑢𝑝 ( 𝐷𝑖𝑒𝑠𝑒𝑙𝑜𝑢𝑡𝑝𝑢𝑡

max 𝑑𝑖𝑒𝑠𝑒𝑙 𝑙𝑜𝑎𝑑𝑖𝑛𝑔) Equation 3.2

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𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑙𝑜𝑎𝑑𝑖𝑛𝑔 𝑜𝑓 𝑒𝑎𝑐ℎ 𝑑𝑖𝑒𝑠𝑒𝑙 =

𝐷𝑖𝑒𝑠𝑒𝑙𝑜𝑢𝑡𝑝𝑢𝑡

𝑛𝑜. 𝑜𝑓 𝑜𝑛𝑙𝑖𝑛𝑒 𝑑𝑖𝑒𝑠𝑒𝑙⁄

𝑑𝑖𝑒𝑠𝑒𝑙 𝑝𝑜𝑤𝑒𝑟 𝑟𝑎𝑡𝑖𝑛𝑔

Equation 3.3

The number of online diesel generators can be identified by rounding up the diesel output over

maximum diesel loading as shown in Equation 3.2, and then the percentage loading of each diesel

can be calculated, followed by fuel consumption and efficiency. (Refer to 2.4.1 Fuel consumption)

44 | P a g e

3.3 Model B – Centralised BESS

Figure 3.2: Model B - Schematic Diagram

As shown in Figure 3.2, Model B has a battery connected to the electricity supplier side, with

renewable generation from the residential roof-mounted PV panels. The primary source of electrical

energy for the load comes from the solar generation through PV panels and inverters. Alternately, if

there is not enough solar generation, the load will draw its power from its secondary source, either

the battery or the diesel generation. The secondary source of electricity depends on a few situations,

as follows:

From the battery

- If the required diesel loading is lower than the diesel is minimum loading and the

battery has the capability to handle the load without going below 50% state of

charge which was kept for spinning reserve.

From the diesel generator

- If the battery state of charge is at or below 50%

From both battery and diesel generator

45 | P a g e

- If the required diesel loading is above the minimum diesel loading, and the battery

can reduce the required diesel loading. The battery support has to be constrained to

prevent the diesel generator from under-loading.

The main source of battery import comes from the excess solar generation after covering the load.

Alternately, if the required diesel loading is below the minimum loading and the battery is not fully

charged, the diesel generator will ramp up the output to the minimum loading to charge the battery.

3.3.1 Solar Characteristics

The solar generation comes from the roof mounted PV panels in the assumed 54 houses at Yalgoo,

and the orientation of the panels are assumed to be in five different directions at 22.5 degrees tilt

angle. The electrical energy generated from the solar panels can be calculated as follows: [50]

𝑆𝑜𝑙𝑎𝑟 𝑜𝑢𝑡𝑝𝑢𝑡 = 𝐴 × 𝑂 × 𝑟 × 𝐻 × 𝐷𝐹 Equation 3.4

Where,

A is the total solar surface area (Refer to 3.1.1 Assumptions)

O is the percentage of total solar panel facing that specified orientation (Refer to 3.1.1 Assumptions)

r is the solar panel efficiency (Refer to 3.1.1 Assumptions)

H is the solar radiation at that hour (Refer to 2.2 Solar Radiation)

DF is the derating factor from PV panel and inverter (Refer to 3.1.1 Assumptions)

Note: The solar radiation depends on the orientation of the panels.

46 | P a g e

3.3.2 Battery Characteristics

The battery characteristics are highly dependent on the diesel generator loading, and it is used to

reduce diesel loading on normal operating conditions and to prevent the diesel generator from

under-loading when the load is low after solar reduction.

The battery export occurs in on two scenarios, first is when the battery state of charge is above the

minimum state of charge and diesel loading is more than minimum diesel loading, then the battery

will be used to reduce the diesel loading. The second is when the available battery capacity is able to

replace an under loaded diesel, going to diesel off-mode.

The charging of the battery comes from two sources, primarily from the excess solar after covering

the load and secondarily from the diesel generators. Diesel will increase loading for battery import if

the battery is at its minimum state of charge and the diesel generator is under loaded.

47 | P a g e

3.3.2.1 Battery Export to Reduce Diesel Loading

The following algorithm is implemented in Excel to calculate the battery export for diesel reduction:

If battery SOC > minimum battery SOC True, % there is enough battery capacity to reduce diesel loading If diesel loading > diesel minimum loading True, % diesel loading can be reduced using battery If battery SOC – minimum battery SOC > diesel loading – diesel minimum loading True, % available battery capacity will cause diesel under loading, thus a limiter must be set Diesel loading – diesel minimum loading False, % available battery will not cause diesel to underload, use all available battery capability to reduce diesel loading Battery SOC – minimum battery SOC False, % diesel is under loading, check if battery has enough capacity to replace the diesel If battery SOC – minimum battery SOC – losses > diesel loading True, % battery is able to act as a virtual diesel and replace the under loading diesel Diesel loading + losses False, % battery is unable to replace the diesel 0 False, % battery can only cover spinning reserve 0

Note: Export losses are included to ensure the battery capacity can handle the load after losses.

48 | P a g e

3.3.2.2 Battery Import to Increase Diesel Loading

The battery import by increase under loading diesel is as follows:

If Battery SOC + battery import from solar < maximum battery SOC True, % after battery import from solar, there is still room for more battery import If load – solar < diesel minimum loading True, % diesel is under loading, increase diesel loading to charge battery If battery export > 0, True, % battery is replacing under loading diesel 0 False, % no battery export If (diesel minimum loading – load – solar) + battery import + battery SOC < Maximum battery SOC True, % increase diesel loading does not overload battery Minimum diesel loading – load – solar False, % increase diesel loading will overload battery Maximum battery charge – battery SOC – battery export False, % diesel is operating above minimum loading 0 False, % battery is fully charged 0

49 | P a g e

3.3.2.3 Battery Import from Excess Solar

Excess solar can be calculated as:

𝐸𝑥𝑐𝑒𝑠𝑠 𝑠𝑜𝑙𝑎𝑟 = 𝑆𝑜𝑙𝑎𝑟𝑜𝑢𝑡𝑝𝑢𝑡 − 𝐿𝑜𝑎𝑑 Equation 3.5

The battery import from excess solar after covering load is as follows:

If excess solar + battery SOC < maximum battery SOC True, % battery capacity can handle all excess solar Excess solar False, % too much solar generation, battery cannot handle it Maximum battery SOC – current battery SOC

3.3.2.4 State of Charge at Start of Hour

Battery state of charge for the next hours, as follows:

𝑆𝑂𝐶𝑛𝑒𝑥𝑡 = 𝑆𝑂𝐶𝑐𝑢𝑟𝑟𝑒𝑛𝑡 − 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑒𝑥𝑝𝑜𝑟𝑡 + 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑖𝑚𝑝𝑜𝑟𝑡𝑑𝑖𝑒𝑠𝑒𝑙

+ 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑖𝑚𝑝𝑜𝑟𝑡𝑠𝑜𝑙𝑎𝑟 Equation 3.6

50 | P a g e


The diesel characteristics for the Model B were created in two steps, first by taking load fluctuation

into consideration. The battery has the ability to cover the load fluctuation caused by a sudden drop

of solar radiation, like a cloudy day, but if the battery is below the minimum state of charge, the

responsibility will be down to the diesel generator. Lastly, the final step is to calculate the required

diesel loading according to the remaining load, battery export and battery import values.

3.3.3.1 Diesel Output with Load Fluctuation

The diesel output with load fluctuation is as follows:

If load + If battery SOC < minimum battery SOC < 0 True, % the battery does not have enough capacity to cover load fluctuation + Load fluctuation False, % the battery covers load fluctuation If solar > battery energy capacity True, % load covered by battery - Battery energy capacity False, % solar covered by solar - Solar True, 0 False, Load + If battery SOC < minimum battery SOC True, + Load fluctuation False, If solar > battery energy capacity True, - Battery energy capacity False, - Solar

51 | P a g e

3.3.3.2 Diesel Output with Solar and Battery Import/Export

The final required diesel output after taking solar and battery into consideration is as follows:

If diesel output (LF) – battery export + battery import < 0 True, % the battery is covering the remaining load after solar deduction Diesel output (LF) – (battery export + losses) + battery import False, % the diesel is either been reduced by battery export or increased to charge battery Diesel output (LF) – (battery export – losses) + battery import

Notes:

1. Diesel output (LF) refers to diesel output with load fluctuation taken into consideration as

calculated in the previous section.

2. For calculation of fuel consumption and diesel efficiency, refer to 2.4.1 Fuel Consumption

and Model A, 3.2.1 Diesel Characteristics.

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3.4 Model C – Distributed BESS

Figure 3.3: Model C - Schematic Diagram

Model C, shown in Figure 3.3, utilises a distributed battery system located in residential houses along

with PV panels and supported by the diesel generator from the electricity supplier. The load draws

the primary source of electricity from the PV panels via the bi-directional inverter and secondary

input from the diesel generators or the battery system. Unlike Model B, the choice of secondary

input depends on time. The price of electricity varies throughout the day due to fluctuating load

demand. Electricity providers classed the fee in two categories, peak and off-peak charge, where

electricity price for the peak period is higher than for the off-peak hours. The peak period set by

Horizon Power is between 1pm to 8pm [51].

The main motivation for a consumer to have solar and battery systems at home is to reduce the

electricity bills. Therefore, the battery has been set up as follows:

1. The batteries import comes from excess solar generations after covering the load

2. The batteries export during the peak electricity period

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3. It will never charge the battery with the grid/diesel generator

3.4.1 Solar Characteristics

The solar characteristics for Model C – distributed BESS is the same as Model B – centralised BESS.

Refer to 3.3 Model B – Centralised BESS for more information.

3.4.2 Battery Characteristics

The battery configuration for Model C is less complex than Model B, as it does not take the under

loading of the diesel generator into consideration. The main purpose of a battery system in a

residential house is to reduce the utility bill and hence the battery stores excess solar for peak period

usage.

3.4.2.1 Battery Export during Peak Electricity Charge

The battery export for Model C is as follows:

If start of peak ≤ time < end of peak True, % battery discharge during peak period to cover remaining load after solar deduction If battery SOC – minimum battery SOC > load – solar + export losses True, % available battery capacity is enough to cover all remaining load after solar deduction (load – solar) + export losses False, % available battery capacity is only enough to cover part of the remaining load after solar deduction Battery SOC – minimum battery SOC False, % it is off-peak period, do not discharge battery to cover load 0

54 | P a g e

Note: Export losses are included to ensure the battery capacity is able to handle the load after losses.

3.4.2.2 Battery Import from Excess Solar

The battery import with excess solar is as follows:

If excess solar + battery SOC < maximum battery SOC True, % the excess solar will not overload the battery Excess solar False, % there is too much solar and battery cannot take all of it Maximum battery SOC – battery SOC

3.4.2.3 State of Charge at Start of Hour

The state of charge for the next hour is as follows:

𝑆𝑂𝐶𝑛𝑒𝑥𝑡 = 𝑆𝑂𝐶𝑐𝑢𝑟𝑟𝑒𝑛𝑡 − 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑒𝑥𝑝𝑜𝑟𝑡 + 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑖𝑚𝑝𝑜𝑟𝑡𝑠𝑜𝑙𝑎𝑟 Equation 3.7

The difference between this calculation and the calculation for Model B is the battery import, as this

equation does not include battery import from diesel.

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The diesel characteristics for Model C are identical to Model B, as it shares the same technique of

calculating diesel output with load fluctuation. The only difference occurs when batteries are added

into the equation because the diesel does not provide electrical energy to the batteries and hence

there will be no addition generation for battery import.

3.4.3.1 Diesel Output with Load Fluctuation

The procedure for diesel output with load fluctuation is the same for both models. Refer to Model B

– Centralised BESS, 3.3.3.1 Diesel Output with Load Fluctuation, for more information.

3.4.3.2 Diesel Output with Solar and Battery Export

The final required diesel output calculation is as follows:

If diesel output (LF) – battery export + battery import < 0 True, % the battery is covering the remaining load after solar deduction Diesel output (LF) – (battery export + losses) False, % the diesel has been reduced by battery export Diesel output (LF) – (battery export – losses)

Notes:

1. Diesel output (LF) refers to diesel output with load fluctuation taken into consideration as

calculated in the previous section.

2. For calculation of fuel consumption and diesel efficiency, refer to 3.3.1 Fuel Consumption

and Model A, 4.2.1 Diesel Characteristics.

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57 | P a g e

Chapter 4 Results & Discussions

The results shown were selective or based on an average value, due to their vast quantity. Refer to

the attached DVD (digital versatile disc), at the back of the booklet, for the energy flow model.

4.1 Solar Radiation

4.1.1 Solar Radiation on Horizontal Surface

4.1.1.1 Solar Data from HOMER

Table 4.1: Total Global Solar Radiation – HOMER

Months Solar Radiation (𝑾/𝒎𝟐)

Average Maximum

Jan 327.02 1262.76

Feb 291.15 1162.13

Mar 245.68 1051.58

Apr 193.13 908.02

May 151.41 824.33

Jun 134.73 729.39

Jul 143.91 766.16

Aug 182.70 944.84

Sept 238.59 1045.10

Oct 292.40 1108.84

Nov 321.18 1234.89

Dec 336.20 1207.63

Annual 237.92 1262.76

Table 4.1 shows the monthly average and maximum total solar radiation of Yalgoo on a horizontal

surface where it was obtained from HOMER simulator. The annual average solar radiation was

237.92 𝑊/𝑚2 with a peak of 1262.76 𝑊/𝑚2 in January. The solar radiation values for summer

were higher because the Sun was directly overhead, at high altitude angle, due to the Earth’s

obliquity and the Earth’s orbit around the Sun.

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4.1.1.2 Solar Radiation with Low Clearness Index

The obtained hourly data based on a horizontal surface were converted mathematically to solar

radiation received by PV panels on a tilted surface at various orientations/azimuth. The conversion

required the total radiation to be divided into diffuse radiation and direct beam radiation. The results

should fulfil the theory mentioned in 2.2.6.3 Ratio of Diffuse Radiation to Direct Beam Radiation.

The philosophy stated that the proportion of diffuse radiation should be higher on an overcast

day/hour, and opposite rationale for clear sky, which are based on the clearness index. Day 5 and

Day 9 were selected to prove that the calculated results are correct.

Figure 4.1: Solar Radiation on Horizontal Surface (Day 5)

Figure 4.1 shows the global solar irradiance, diffuse solar radiation and direct beam radiation of Day

5. It has an average global radiation of 183.01 𝑊/𝑚2 and an hourly average peak of 658.99 𝑊/𝑚2

at noon. Day 5 was a summer day, but yet it had a low average and peak solar radiation with an

average clearness index of 0.41, indicating that it was a cloudy day. The calculated diffuse solar

radiation holds a major percentage of the total radiation, proved the calculations were done correctly,

0

100

200

300

400

500

600

700

00:00:00 06:00:00 12:00:00 18:00:00 00:00:00

So

lar

Rad

iati

on

(𝑊

/𝑚

^2)

Time

Solar Radiation - Horizontal Surface (Day 5)

Global solarradiation,IH

Diffusesolarradiation, Id

Direct beamsolarradiation, Ib

59 | P a g e

as it fits the theory stated in the background. At 1300 hours, the clearness index plunged to 0.12

with direction beam radiation down to just 3.98 𝑊/𝑚2, specifies that it may be raining or a majority

of the sky was covered. Refer to Appendix, Table 7.1: Solar Data for Day 5 - Overcast Sky for more

information.

4.1.1.3 Solar Radiation with High Clearness Index

Figure 4.2: Solar Radiation on Horizontal Surface (Day 9)

In contrast, Day 9 shows a higher global solar radiation than Day 5, with an average clearness index

of 0.77, indicating that it was a day with a relatively clear sky. Figure 4.2 displays the proportion of

direct beam radiation was significantly greater than the diffuse radiation, as predicted by the theory

mentioned in Chapter 2 – Background. Refer to Table 7.2: Solar Data for Day 9 - Clear Sky for

more information.

0

200

400

600

800

1000

1200

1400

00:00:00 06:00:00 12:00:00 18:00:00 00:00:00

So

lar

Rad

iati

on

(𝑊

/𝑚

^2)

Time

Solar Radiation - Horizontal Surface (Day 9)

Global solarradiation,IH

Diffusesolarradiation, Id

Direct beamsolarradiation, Ib

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4.1.2 Solar Radiation on Tilted Surface

4.1.2.1 Solar Radiation of Various Orientations during Summer

The comparison of the solar radiation of various orientations can determine if the solar conversion

was done correctly. During summer, the altitude of the Sun is high, with the Sun path directly

overhead, and therefore resulting in higher solar radiation on a horizontal surface than a tilted

surface. For this analysis, Day 9 has been chosen due to its high clearness index.

Figure 4.3: Solar Radiation – Summer (Day 9)

According to Figure 4.3, between 1200 to 1300 hours, the solar radiation on a horizontal surface was

higher than any other orientations. The radiation on a north facing panel was slightly lower than the

horizontal surface, indicating that the ideal tilt angle is between 0° to 22.5° (roof pitch angle). Lastly,

the radiation on an east facing panel peaked in the morning while west facing panel peaked after

0

200

400

600

800

1000

1200

1400

00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 00:00:00

So

lar

Rad

iati

on

(𝑊

/𝑚

^2)

Time

Solar Radiation - Summer (Day 9)

HorizontalSurface

West

North-west

North

North-east

East

61 | P a g e

noon, and hence these results verified that the azimuths used were correct. Refer to Table 7.3: Solar

Radiation of Various Orientations (Day 9) for more details.

4.1.2.2 Solar Radiation of Various Orientations during Winter

Figure 4.4: Solar Radiation – Winter (Day 190)

Figure 4.4 is the graph of solar radiation at various orientations during winter on Day 190, and the

radiation level is higher for the north facing panel because the altitude of the Sun is lower. The solar

radiation for various orientations peaked as expected, following the path of the Sun. According to

the results of both summer and winter, the conversion of solar radiation on a horizontal surface to a

tilted surface reflected the technically expected results. Refer to Table 7.4: Solar Radiation of Various

Orientations (Day 190) for more details.

0

200

400

600

800

1000

1200

00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 00:00:00

So

lar

Rad

iati

on

(𝑊

/𝑚

^2)

Time

Solar Radiation - Winter (Day 190)

HorizontalSurface

West

North-west

North

North-east

East

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4.1.3 Solar Generation

Table 4.2: Solar Generation of Various Orientations

Orientation Solar Generation (kWh)

Average per hour (𝒌𝑾/𝒎𝟐) Total per year (𝒌𝑾/𝒎𝟐)

West 4.96 43407.97

North-west 5.42 47488.32

North 5.82 50941.07

North-east 5.91 51757.68

East 5.66 49548.71

Overall 27.76 243143.8

The total solar generations for both Model B and Model C were calculated using the equation and

assumptions based on Chapter 3 Methodology. Table 4.2 shows that the system has a annual

generation of 243 MWh with an hourly average of 27.76 kWh. The total solar generation is 24.4% of

the total load, 996 MWh.

Table 4.3: Solar Energy Flow

Solar Generation (kWh)

Cover load 237962

Excess solar 5181

238 MWh of the total solar generation were used to cover the load, leaving the remaining 5181 kWh

of generated energy as excess solar and these excess solar energies were then used to charge the

battery.

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4.2 Battery

4.2.1 Model B – Centralised BESS

Table 4.4: Centralised BESS - Battery Energy Flow

Battery export to reduce diesel loading (kWh) 28342

Battery import from diesel (kWh) 25917

Battery import from solar (kWh) 3916

Excess solar to dump load (kWh) 1264

Table 4.4 shows the energy flow model results of the centralised BESS, and the results are excluding

the energy losses from charging and discharging of the battery. Overall, the battery exported 28

MWh of electricity to reduce diesel loading and imported 259 MWh of energy from diesel to prevent

it from under loading. 3916.26 kWh of the excess solar holds 13.1% of the total import, while the

remaining 1264.84 kWh was wasted due to the situation where the system experienced low load,

high solar generation and a fully charged battery system. Thus, this shows that there was either too

much solar generation or the selected battery capacity was too small for the power network.

Table 4.5: Battery Energy Flow of Various Battery Size

Battery Size

164kW/164kWh 300kW/300kWh 400kW/400kWh

Battery export to reduce diesel loading (kWh) 28342.01 29328.58 29466.04

Battery import from diesel (kWh) 25917.44 25835.97 25835.97

Battery import from solar (kWh) 3916.26 5036.23 5180.92

Excess solar to dump load (kWh) 1264.84 144.87 0.18

The fuel consumption will increase if the solar generation is reduced, and hence it is more sensible

to increase the battery storage. According to Table 4.5, the amount of excess solar energy to dump

load reduced with the increment of battery capacity, but it is not necessarily ideal to have the largest

battery storage. For example, the amount of excess solar power to dump load, for 300kW and

400kW systems, reduced from 144.87 kWh to 0.18 kWh, but the battery imports and export are

identical. Therefore, it will be more economical to have smaller battery storage of 300kW along with

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a small dump load than a 400kW battery system. The increment of battery capacity from 164 kWh

to 300kWh also indicates a reduction in diesel fuel consumption as the amount of battery import

from the diesel reduced. In addition to that, the battery capacity of 400 kWh required the same

quantity of import from the diesel generation as 300 kWh systems, verified that a 300 kWh battery

system is sufficient.

4.2.2 Model C – Distributed BESS

Table 4.6: Distributed BESS - Battery Energy Flow

Battery export to reduce diesel loading (kWh) 4396.90

Battery import from solar (kWh) 4628.32

Excess solar to dump load (kWh) 552.78

Table 4.6 shows the energy flow results of distributed batteries with the exclusion of charge and

discharge energy losses. The energy flow was significantly less than Model B - centralised BESS,

since there was no import from the diesel, with total export at 4396.9 kWh and import at 4628.32

kWh from excess solar generation. 552.78 kWh of the excess solar generated electricity went to the

dump load, due to high solar generation, low load and fully charged battery. Despite having excess

solar power going to the dump load, the amount of energy flow indicates that the battery state of

charge remained at 50% most of the time as there was not enough solar generation.

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4.3 Diesel

Model A – diesel only was set as the base model to compare the influence on the diesel sets with the

addition of solar and battery, and it was expected to consume more fuel as diesel is the only source

of power for the load.

Table 4.7: Diesel Energy Flow

Model A

Diesel only Model B

Centralised BESS Model C

Distributed BESS

Fuel consumption 255774 Litre 203118 Litre 202454 Litre

-20.59%

-20.85%

Average diesel fuel

efficiency 3.87 kWh/L 3.74 kWh/L 3.58 kWh/L

Energy generated 996132 kWh 757124 kWh 753987 kWh

Number of hours operating with zero

diesel 0 hours 1112 hours 0 hours

Number of hours operating below

minimum loading 561 hours 0 hours 2735 hours

According to the simulation results shown in Table 4.7, the total fuel consumption for the base

model is 255774.78 litres, and roughly 20% less for both Model B and Model C, with Model B

consumed slightly more than Model C.

The major difference between the models was the number of hours operating below minimum

loading. The base model operated 561 hours below the minimum diesel loading, while Model B and

Model C operated 0 hours and 2735 hours respectively. Model B had 0 hours caused by the battery

characteristic, the diesel either increased loading to charge the battery or went to diesel off-mode

with the support of the battery, the virtual diesel generator. That resulted in 1112 hours of the year

where the electricity network was fully supported by the battery and solar generation.

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Meanwhile, Model C had an increment of 2174 hours from the base model due to battery discharge

characteristic during peak electricity hours, which explained why it has the lower fuel efficiency level

among all models.

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Chapter 5 Conclusion

5.1 Summary

In conclusion, the energy flow model was a success as it produced the expected results. Model B,

centralised BESS, suggested being a better system for Yalgoo, Western Australia. Despite using

more fuel than Model C, Model B provides more functions and advantages as following:

1. The centralised BESS can be used as a virtual diesel

2. Able to operate the electricity network with diesel off-mode

3. Prevent diesel from under loading by inducing battery import

4. Easy to upgrade in the future as electricity supplier holds the ownership

5. Spinning reserve coverage for entire community

Other than that, centralised BESS has plenty of useful functions such as voltage control, frequency

control, black start, peak shaving and short-term load fluctuation. Furthermore, because the

electricity provider owns the battery system, battery energy storage system has more prospects for

future expansion. In comparison, Model C – distributed BESS can only apply those functions in the

participating houses.

Therefore, in terms of both functionality and economically, Yalgoo is more suitable for Model B –

centralised battery energy storage system.

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5.2 Future Work

There are a few possible future works for this project:

1. Economic analysis

2. PowerFactory simulation

3. Centralised BESS expansion

Economic analysis is an essential approach to determine if the systems are realistic for the next

phase, other than been logically or mechanically achievable. Furthermore, the models can be

simulated in PowerFactory for various scenarios to test the capability and flexibility of each model,

scenarios such as tripping of diesel, an extended period of no solar input and sudden peak in load

demand. The simulator can also provide an extended feasibility investigation if the additional setup

will affect the quality of the existing network like voltage rise or power factor influences, and hence

identify the potential upgrade needed in parallel with the setup.

The energy flow models of the centralised BESS can also be further expanded. The results show

that a bigger battery capacity is preferable for centralised energy storage in Yalgoo, but it is not

possible to substitute the diesel generator completely. Thus, the expansion should seek an alternative

method to operate the network with pure renewable resources by increasing the capacity of both the

solar panels and the battery and discover the balance for the network. Subsequently, a sky camera

can be added into the equation for short-term solar forecasting to maximise the usage of the hybrid

system.

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Chapter 7 Appendices

7.1 Datasheets

The highlighted data shown in Figure 7.1, 7.3 and 7.4 are the chosen parameters.

7.1.1 Diesel Generator – Cummins QLS9-G5

Figure 7.1: Diesel Output [45]

Figure 7.2: Diesel Specifications [45]

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Figure 7.3: Diesel Dimensions and Fuel Consumption [45]

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7.1.2 Solar Panel - LDK 250 PA

Figure 7.4: PV Panel Specifications [47]

Figure 7.5: PV Panel Mechanical Characteristics [47]

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7.2 Solar Radiation

7.2.1 Day 5 – Solar Data

Table 7.1: Solar Data for Day 5 - Overcast Sky

Time Global solar radiation, IH

Clearness index, kT

Diffuse solar radiation, Id

Direct beam solar radiation, Ib

00:00:00 0.00 0.00 0.00 0.00

01:00:00 0.00 0.00 0.00 0.00

02:00:00 0.00 0.00 0.00 0.00

03:00:00 0.00 0.00 0.00 0.00

04:00:00 0.00 0.00 0.00 0.00

05:00:00 18.02 0.87 18.02 0.00

06:00:00 134.20 0.42 105.78 28.41

07:00:00 275.95 0.45 205.96 69.99

08:00:00 369.32 0.42 292.36 76.96

09:00:00 364.96 0.33 323.43 41.53

10:00:00 516.44 0.40 418.52 97.91

11:00:00 453.48 0.33 401.86 51.62

12:00:00 658.99 0.47 471.51 187.48

13:00:00 165.37 0.12 161.39 3.98

14:00:00 422.93 0.35 368.25 54.68

15:00:00 430.06 0.42 339.73 90.33

16:00:00 337.11 0.43 260.07 77.04

17:00:00 173.10 0.35 150.44 22.66

18:00:00 70.28 0.36 60.71 9.57

19:00:00 2.12 0.00 2.11 0.02

20:00:00 0.00 0.00 0.00 0.00

21:00:00 0.00 0.00 0.00 0.00

22:00:00 0.00 0.00 0.00 0.00

23:00:00 0.00 0.00 0.00 0.00

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7.2.2 Day 9 – Solar Data

Table 7.2: Solar Data for Day 9 - Clear Sky

Time Global solar radiation, IH

Clearness index, kT

Diffuse solar radiation, Id

Direct beam solar radiation, Ib

00:00:00 0.00 0.00 0.00 0.00

01:00:00 0.00 0.00 0.00 0.00

02:00:00 0.00 0.00 0.00 0.00

03:00:00 0.00 0.00 0.00 0.00

04:00:00 0.00 0.00 0.00 0.00

05:00:00 23.75 1.00 23.75 0.00

06:00:00 201.76 0.66 71.26 130.49

07:00:00 377.37 0.63 156.41 220.96

08:00:00 567.50 0.65 211.00 356.50

09:00:00 761.20 0.69 228.32 532.88

10:00:00 1057.28 0.83 130.07 927.21

11:00:00 1092.27 0.80 172.44 919.83

12:00:00 1222.72 0.87 111.06 1111.66

13:00:00 1207.27 0.90 92.92 1114.36

14:00:00 1039.20 0.85 110.47 928.73

15:00:00 849.62 0.83 107.43 742.19

16:00:00 613.41 0.79 103.43 509.98

17:00:00 362.32 0.73 89.37 272.94

18:00:00 124.86 0.62 53.67 71.19

19:00:00 2.05 0.00 2.03 0.02

20:00:00 0.00 0.00 0.00 0.00

21:00:00 0.00 0.00 0.00 0.00

22:00:00 0.00 0.00 0.00 0.00

23:00:00 0.00 0.00 0.00 0.00

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7.2.3 Day 9 – Tilted Surface

Table 7.3: Solar Radiation of Various Orientations (Day 9)

Time

Solar Radiation (Wh/m2)

Horizontal Surface

Tilted Surface

West North-west North North-east East

00:00:00 0.00 0.00 0.00 0.00 0.00 0.00

01:00:00 0.00 0.00 0.00 0.00 0.00 0.00

02:00:00 0.00 0.00 0.00 0.00 0.00 0.00

03:00:00 0.00 0.00 0.00 0.00 0.00 0.00

04:00:00 0.00 0.00 0.00 0.00 0.00 0.00

05:00:00 23.75 23.11 23.11 23.11 23.11 23.11

06:00:00 201.76 70.85 70.85 70.85 439.28 612.02

07:00:00 377.37 154.76 154.76 291.94 516.56 598.26

08:00:00 567.50 320.84 357.91 500.95 695.64 756.78

09:00:00 761.20 515.49 565.54 706.45 880.55 925.79

10:00:00 1057.28 772.01 845.39 1005.72 1182.35 1215.64

11:00:00 1092.27 910.80 966.56 1058.40 1141.64 1145.52

12:00:00 1222.72 1113.87 1155.95 1193.28 1201.72 1181.80

13:00:00 1207.27 1203.23 1213.50 1176.44 1100.01 1062.16

14:00:00 1039.20 1128.36 1101.86 1001.74 866.16 823.97

15:00:00 849.62 1009.80 949.02 800.21 626.69 587.68

16:00:00 613.41 807.26 722.78 553.29 375.60 348.05

17:00:00 362.32 541.44 453.59 300.53 155.18 143.11

18:00:00 124.86 219.84 167.45 86.57 53.05 53.05

19:00:00 2.05 1.97 1.97 1.97 1.97 1.97

20:00:00 0.00 0.00 0.00 0.00 0.00 0.00

21:00:00 0.00 0.00 0.00 0.00 0.00 0.00

22:00:00 0.00 0.00 0.00 0.00 0.00 0.00

23:00:00 0.00 0.00 0.00 0.00 0.00 0.00

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7.2.4 Day 190 – Tilted Surface

Table 7.4: Solar Radiation of Various Orientations (Day 190)

Time

Solar Radiation (Wh/m2)

Horizontal Surface

Tilted Surface

West North-west North North-east East

00:00:00 0.00 0.00 0.00 0.00 0.00 0.00

01:00:00 0.00 0.00 0.00 0.00 0.00 0.00

02:00:00 0.00 0.00 0.00 0.00 0.00 0.00

03:00:00 0.00 0.00 0.00 0.00 0.00 0.00

04:00:00 0.00 0.00 0.00 0.00 0.00 0.00

05:00:00 0.00 0.00 0.00 0.00 0.00 0.00

06:00:00 0.00 0.00 0.00 0.00 0.00 0.00

07:00:00 57.89 56.35 56.35 56.35 56.35 56.35

08:00:00 261.50 53.66 142.49 494.02 711.78 641.24

09:00:00 462.60 121.22 408.40 711.09 850.24 748.53

10:00:00 584.42 343.21 597.56 823.86 876.07 756.14

11:00:00 703.32 531.84 789.33 971.27 943.98 788.89

12:00:00 688.77 620.78 827.88 929.34 831.10 674.31

13:00:00 660.03 680.80 859.03 897.34 729.47 559.52

14:00:00 590.06 702.64 852.85 827.81 588.90 404.72

15:00:00 386.71 536.45 621.97 556.30 332.87 191.27

16:00:00 169.59 280.40 310.23 252.45 115.26 54.08

17:00:00 13.35 13.44 13.48 13.24 12.88 12.88

18:00:00 0.00 0.00 0.00 0.00 0.00 0.00

19:00:00 0.00 0.00 0.00 0.00 0.00 0.00

20:00:00 0.00 0.00 0.00 0.00 0.00 0.00

21:00:00 0.00 0.00 0.00 0.00 0.00 0.00

22:00:00 0.00 0.00 0.00 0.00 0.00 0.00

23:00:00 0.00 0.00 0.00 0.00 0.00 0.00

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