expansion study and performance analysis...

E X PA N S I O N S T U D Y A N D

P E R F O R M A N C E A N A LY S I S O F T H E

D E N M A R K C O M M U N I T Y W I N D FA R M

THESIS PROJECT

Thesis submitted to the School of Engineering and Information Technology, Murdoch University in partial fulfilment of the requirements for the degree of:

Bachelor of Engineering Honours [BE(Hons)] Electrical Power & Renewable Energy

M U R D O C H U N I V E R S I T Y

S C H O O L O F E N G I N E E R I N G A N D I N F O R M A T I O N T E C H N O L O G Y

E N G 4 7 0 E N G I N E E R I N G H O N O U R S T H E S I S

A I D E N J A M E S S T A N K O V I C

J A N U A R Y 2 0 1 7

DECLARATION

I, Aiden James Stankovic, certify that this work contains no material which has been

accepted for the award of any other degree or diploma in my name, in any university

or other tertiary institution and, to the best of my knowledge and belief, contains no

material previously published or written by another person, except where due

reference has been made in the text.

In addition, I certify 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 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.

Signed: …………………………………………………..

Name: ……………………………………………………

Date: ……………………………………………………..

ACKNOWLEDGEMENTS

Firstly, I would like to express my sincere gratitude to my supervisor and educator,

Dr. Martina Calais, for your continued guidance and support, not only during this

thesis project, but throughout the course of my engineering degree. Your passion for

teaching electrical and renewable engineering has inspired me to work just as hard

to learn. I feel like I am now ready to grasp my engineering career with both hands.

Adj. Professor Craig Carter, your energy and enthusiasm is incredible. You have

given so much of your own time for this project, and for that I am truly thankful.

Your knowledge of the industry brings an aspect to university that I believe every

undergraduate should be exposed to. I am leaving university with skills that I would

not have gained without your time and efforts.

Special thanks must also be awarded to Andrew Woodroffe from SkyFarming. You

have had some brilliant ideas that I would not have thought of by myself, and your

zealousness has always kept me interested in this project.

Last, but certainly not least, thank you to my beautiful partner, Brittany. You have

always been there for me, through the late nights, the early mornings, the good

times, and the terrible. Through everything, you have never left my side. You bring

out the best in me, and I would not be where I am without your patience, kindness,

and understanding.

vii

ABSTRACT

Integration of renewable energy generators into rural distribution networks can

cause significant problems with voltage rise at the point of connection during times

of maximum generation. One such case is the Denmark Community Windfarm,

where the rated power of the wind farm has been limited to 90% in order to keep

network voltages within acceptable limits. Expansion of the wind farm is forecast by

the wind farm operator due to the location’s good wind resource, and therefore

overcoming this restriction is required.

A generation analysis has determined that the wind farm does not currently lose

much annual production due to the imposed maximum power limit. However, the

implementation of an additional wind turbine generator results in substantial

impact on the wind farm’s annual production. A battery energy storage system can

limit the amount of wasted generation from the expanded wind farm, but such

systems are expensive for utility-scale utilisation and so are not yet economically

feasible to implement.

Modern wind turbine generator technology can provide dynamic reactive power

support to the distribution network. Application of such machines allows the wind

farm to generate at its full potential whilst keeping network voltages within

acceptable limits. This is confirmed through simulation of the Denmark distribution

network.

ix

TABLE OF CONTENTS

DECLARATION ..................................................................................................................... III

ACKNOWLEDGEMENTS ........................................................................................................ V

ABSTRACT ........................................................................................................................... VII

TABLE OF CONTENTS ........................................................................................................... IX

LIST OF FIGURES ................................................................................................................ XIII

LIST OF TABLES ................................................................................................................... XV

LIST OF ACRONYMS AND ABBREVIATIONS ......................................................................... XVII

UNITS ................................................................................................................................ XIX

INTRODUCTION ................................................................................................................... 1

1.1 Purpose ..................................................................................................................................... 1 1.2 Aims and Objectives .................................................................................................................. 1 1.3 Thesis Structure ......................................................................................................................... 3

1.3.1 Wind Generation Analyses ..................................................................................................... 3 1.3.2 BESS Analysis.......................................................................................................................... 3 1.3.3 Overcoming Restrictive Power Limitations ............................................................................ 3 1.3.4 Simulation of Network Voltages ............................................................................................ 3

2. BACKGROUND .............................................................................................................. 5

2.1 Denmark Community Windfarm History .................................................................................... 6 2.2 Denmark Community Windfarm Turbines ................................................................................. 7 2.3 Denmark Region Distribution Network ...................................................................................... 8 2.4 Network Voltage Rise ................................................................................................................ 9 2.5 Battery Energy Storage Systems .............................................................................................. 10

3. WIND GENERATION ANALYSES .................................................................................. 13

3.1 Data Used in Analysis .............................................................................................................. 14 3.2 Generation Analysis – Two WTGs Restricted ........................................................................... 16

3.2.1 Method 1 - ENERCON SCADA System ................................................................................... 16 3.2.2 Method 2 - ENERCON Power Curve ...................................................................................... 17 3.2.3 Method 3 – Western Power Meter Data .............................................................................. 21 3.2.4 Two WTGs Restricted Analysis Results ................................................................................. 21

3.3 Generation Analysis – Two WTGs Unrestricted ........................................................................ 25 3.3.1 Two WTGs Unrestricted Analysis Methodology ................................................................... 25 3.3.2 Two WTGs Unrestricted Analysis Results ............................................................................. 26

3.4 Generation Analysis – Three WTGs Restricted ......................................................................... 27

x

3.4.1 Three WTGs Restricted Analysis Methodology .................................................................... 27 3.4.2 Three WTGs Restricted Analysis Results .............................................................................. 28

3.5 Generation Analysis – Three WTGs Unrestricted ..................................................................... 29 3.5.1 Three WTGs Unrestricted Analysis Methodology ................................................................ 29 3.5.2 Three WTGs Unrestricted Analysis Results ........................................................................... 29

3.6 Effect of Increasing Power Limitation ...................................................................................... 31 3.7 DCWF Capacity Factor.............................................................................................................. 32 3.8 Third WTG Site......................................................................................................................... 33 3.9 Third WTG Economic Analysis .................................................................................................. 36

4. BESS ANALYSIS ......................................................................................................... 39

4.1 BESS Size .................................................................................................................................. 40 4.2 BESS Type ................................................................................................................................ 42

4.2.1 Vanadium Redox Battery Option ......................................................................................... 43 4.2.2 Lithium-Ion Battery Option .................................................................................................. 46

4.3 BESS Generation Analysis ........................................................................................................ 50 4.3.1 Maximum Generation Mode ................................................................................................ 50 4.3.2 DCWF Output with BESS in MGM ........................................................................................ 53 4.3.3 Peak Shaving Mode .............................................................................................................. 56

4.4 BESS Economic Analysis ........................................................................................................... 59 4.4.1 BESS Pricing .......................................................................................................................... 59 4.4.2 BESS Payback ....................................................................................................................... 61

5. OVERCOMING RESTRICTIVE POWER LIMITATIONS ..................................................... 67

5.1 BESS Inverter ........................................................................................................................... 67 5.2 STATCOM ................................................................................................................................ 67 5.3 ENERCON WTG Technology ..................................................................................................... 68

6. SIMULATION OF NETWORK VOLTAGES ...................................................................... 71

6.1 PowerFactory Model ............................................................................................................... 72 6.2 Simulation of Original Network ............................................................................................... 73 6.3 Simulation of Two WTGs – Limited Output .............................................................................. 75 6.4 Simulation of Two WTGs – Maximum Output .......................................................................... 76 6.5 Simulation of Three WTGs – Limited Output............................................................................ 77 6.6 Simulation of Three WTGs – Maximum Output ....................................................................... 78 6.7 Simulation of Three WTGs with Q+ and STATCOM Option – No Output .................................. 79 6.8 Simulation of Three WTGs with STATCOM Option – Limited Output ....................................... 80 6.9 Simulation of Three WTGs with STATCOM Option – Maximum Output ................................... 81

7. PROJECT COMPLICATIONS ......................................................................................... 83

8. CONCLUSION ............................................................................................................. 85

9. REFERENCES............................................................................................................... 87

10. LITERATURE REVIEW ............................................................................................. 91

10.1 Developing Wind Power Projects ........................................................................................ 91

xi

10.2 Urban Wind Energy ............................................................................................................. 91 10.3 Electricity Generation Using Wind Power ............................................................................ 92 10.4 ENERCON E-48 Datasheet.................................................................................................... 92 10.5 Wind Resource Assessment: A Practical Guide to Developing a Wind Project ..................... 93 10.6 Denmark Community Wind Farm Study Summary .............................................................. 93 10.7 Voltage Impact Studies Investigating Reactive Power Control Modes of Inverter-Coupled Wind Generation Connected to a Weak Rural Feeder ....................................................................... 94 10.8 Design and Analysis of Large Lithium-Ion Battery Systems .................................................. 94

11. APPENDICES ............................................................................................................... 95

11.1 Appendix A: ENERCON E-48 WTG Specifications ................................................................. 95 11.2 Appendix B: Powerfactory Model Parameters .................................................................... 96

xiii

LIST OF FIGURES

Figure 1: DCWF Site ................................................................................................................ 5

Figure 2: DCWF Construction ................................................................................................. 6

Figure 3: Anemomter at Mt Barker Wind Farm ..................................................................... 7

Figure 4: Simplified Denmark Region Distribution Network .................................................. 8

Figure 5: ENERCON E-48 Formulated Power Curve.............................................................. 19

Figure 6: Comparison of Results from Analysis Methods .................................................... 23

Figure 7: Two WTGs Limited and Unlimited Operation ....................................................... 26

Figure 8: Two and Three WTGs Limited and Unlimited Operation ...................................... 30

Figure 9: Sensitivity Analysis of Annual Generation with Increasing Power Limitation ...... 31

Figure 10: Wind Rose of the DCWF Site ............................................................................... 34

Figure 11: Possible Locations for T3 ..................................................................................... 35

Figure 12: Third WTG Payback Period .................................................................................. 38

Figure 13: Battery Power Selection ...................................................................................... 40

Figure 14: Annual Output of BESS with Inreasing Battery Capacity ..................................... 41

Figure 15: Vanadium Redox Battery Technology ................................................................. 44

Figure 16: Lithium-Ion Battery Technology .......................................................................... 47

Figure 17: DCWF Best Week of Generation ......................................................................... 53

Figure 18: DCWF Worst Week of Generation ...................................................................... 54

Figure 19: DCWF Average Week of Generation ................................................................... 55

Figure 20: Payback Period for BESS Expansion in 2017 ........................................................ 65

Figure 21: Payback Period for BESS Expansion in 2020 ........................................................ 66

Figure 22: Conventional E-48 WTG P-Q Characterisitc ........................................................ 68

Figure 23: E-48 WTG with Q+ P-Q Characteristic ................................................................. 69

Figure 24: WTG with Q+ and STATCOM P-Q Characteristic ................................................. 70

Figure 25: PowerFactory Simulated Network ...................................................................... 72

Figure 26: Simulation of Original Network ........................................................................... 74

Figure 27: Simulation of Two WTGs - Limited Output ......................................................... 75

xiv

Figure 28: Simulation of Two WTGs – Maximum Output .................................................... 76

Figure 29: Simulation of Three WTGs - Limited Output ....................................................... 77

Figure 30: Simulation of Three WTGs - Maximum Output ................................................... 78

Figure 31: Simulation of Three WTGs with Q+ and STATCOM - No Output ........................ 79

Figure 32: Simulation of Three WTGs with Q+ and STATCOM - Limited Output ................. 80

Figure 33: Simulation of Three WTGs with Q+ and STATCOM - Maximum Output ............. 81

xv

LIST OF TABLES

Table 1: WTG Output Power Over Different Wind Speeds .................................................. 18

Table 2: Summary of Generation Analyses .......................................................................... 23

Table 3: Capacity Factors of Different System Options ........................................................ 32

Table 4: NPC of Third WTG Expansion .................................................................................. 37

Table 5: Utility-Scale Vanadium Redox Battery Advantages ................................................ 44

Table 6: Utility-Scale Vanadium Redox Battery Disadvantages ........................................... 45

Table 7: Gildemeister CellCube 250-1000 Specifications ..................................................... 46

Table 8: Utility-Scale Lithium-Ion Battery Advantages ......................................................... 47

Table 9: Utility-Scale Lithium-Ion Battery Disadvantages .................................................... 48

Table 10: Tesla Powerpack 2.0 Specifications ...................................................................... 48

Table 11: Maximum Generation Mode Control Logic .......................................................... 51

Table 12: BESS Energy Flow Simulation Results – Maximum Generation Mode ................. 52

Table 13: Peak Shaving Mode Control Logic ........................................................................ 57

Table 14: BESS Energy Flow Simulation Results – Peak Shaving Mode ............................... 58

Table 15: NPC of BESS Expansion ......................................................................................... 61

Table 16: DCWF Revenue with Third WTG and BESS ........................................................... 64

Table 18: Simulation of Original Network Results ................................................................ 74

Table 19: Simulation Results of Two WTGs - Limited Output .............................................. 75

Table 20: Simulation Results of Two WTGs – Maximum Output ......................................... 76

Table 21: Simulation Results of Three WTGs - Limited Output ............................................ 77

Table 22: Simulation Results of Three WTGs - Maximum Output ....................................... 78

Table 22: Simulation Results of Three WTGs with Q+ and STATCOM - No Output ............. 79

Table 23: Simulation Results of Three WTGs with Q+ and STATCOM - Limited Output ...... 80

Table 24: Simulation Results of Three WTGs with Q+ and STATCOM - Maximum Output . 81

Table 26: ENERCON E-48 WTG Power Produced Over Different Wind Speeds ................... 95

Table 27: PowerFactory Network Parameters ..................................................................... 96

xvii

LIST OF ACRONYMS AND ABBREVIATIONS

ARENA Australian Renewable Energy Agency

BESS(s) Battery Energy Storage System

BRCP Benchmark Reserve Capacity Price

DCW Denmark Community Windfarm

DoD Depth of Discharge

ESS ENERCON SCADA system

LDF Lower Denmark Feeder

LIB(s) Lithium-Ion Battery(s)

LGC(s) Large-scale Energy Certificate(s)

POC Point of Connection

MGM Maximum Generation Mode

MV Medium Voltage

NPC Net Present Cost

NPV Net Present Value

O&M Operation and Maintenance

POC Point of Connection

POE Price of Electricity

PSM Peak Shaving Mode

PPA Power Purchase Agreement

REC(s) Renewable Energy Certificate(s)

xviii

SCADA Supervisory Control and Data Acquisition

STEM Short Term Energy Market

SWIS South West Interconnected System

T1 Turbine 1

T2 Turbine 2

T3 Turbine 3

VRB(s) Vanadium Redox Battery(s)

WEM Wholesale Electricity Market

WTG(s) Wind Turbine Generator(s)

xix

UNITS

A Ampere

°C Degrees Celsius

m Metre

s Second

m/s Metre/Second

km Kilometre

kV Kilovolt

kW Kilowatt

kWh Kilowatt Hour

m2 Squared Metre

ms Millisecond

MW Megawatt

MWh Megawatt Hour

MVAr Mega Volt-Ampere reactive

T Ton

V Volt

1

INTRODUCTION

1.1 Purpose

The purpose of this report is to document the engineering thesis project undertaken

by Aiden James Stankovic in partial fulfilment of the requirements of a Bachelor of

Engineering Honours degree at Murdoch University.

1.2 Aim and Objectives

The Denmark Community Windfarm (DCWF) is a wind farm located in Denmark,

Western Australia currently comprising of two 800 kW ENERCON E-48 wind

turbine generators (WTGs). Due to the location of the wind farm on the Denmark

distribution network, the wind farm faces current issues with network voltage rise at

the point of connection (POC) at times of maximum output. Consequently the

power limit of the WTGs has been limited to 90% of rated capacity, 720 kW, and the

WTGs are required to operate at a fixed power factor of 0.9 absorbing.

The DCWF Board has requested an investigation into the expansion of the DCWF.

The implementation of a third ENERCON E-48 WTG has been proposed as an

expansion option to the wind farm. The possible inclusion of a battery energy

storage system (BESS) has also been considered as an option to develop the DCWF.

2

In order to maximise the potential generation from the DCWF, the power limitation

from the wind farm will be attempted to be raised. The aim of this thesis is to

investigate different options to raise the maximum power limit of the DCWF and

each option tested for effectiveness. Simulations of the network will ultimately be

carried out to test the impact of different limit-raising options on the network

voltage.

An economic analysis will also be carried out on proposed expansion options. Net

present cost (NPC), net present value (NPV), and payback period of the different

system options will be calculated to determine their economic feasibility.

The objectives of the thesis project can be summarised below:

• Perform a generation analysis of the current operation of the DCWF;

• Perform a generation analysis of the expanded operation of the DCWF with a

third WTG;

• Research and determine an appropriate type, size, and make and model of

battery storage product;

• Perform a generation analysis of the expanded operation of the DCWF with

the inclusion of the BESS;

• Carry out an economic analysis of different expansion options; and

• Simulate different expansion options to determine effect on network voltage.

3

1.3 Thesis Structure

The thesis project report body has been broken down into four main sections. This is

due to the individual methodologies and broad nature of the project. Itemisation of

the various section components is shown below.

1.3.1 Wind Generation Analyses

• Generation analysis of the DCWF with and without power restrictions.

• Generation analysis of the expanded DCWF with third WTG.

• Economic analysis of third WTG.

1.3.2 BESS Analysis

• BESS size and type selection.

• Generation analysis of the expanded DCWF with third WTG and BESS.

• Economic analysis of BESS.

1.3.3 Overcoming Restrictive Power Limitations

• Q+ and STATCOM option for this WTG.

• BESS inverter reactive power capabilities.

1.3.4 Simulation of Network Voltages

• Simulation of network voltages to assess impact of investigated expansion

options.

5

2. BACKGROUND

The Denmark Community Windfarm (DCWF) is located approximately 400 km

south of Perth, 10 km south of the town of Denmark, in the Great Southern region of

Western Australia. Figure 1 shows the layout of the DCWF site, encompassing both

WTGs, Turbine 1 (T1) and Turbine 2 (T2); the electrical switch-room; and the

constructed roads on the site [1]. (Image used with author’s permission)

Figure 1: DCWF Site

6

2.1 Denmark Community Windfarm History

The DCWF is a community owned project, and is operated by Denmark Community

Windfarm Ltd [2]. First concepts of the project began in 2003, when the Denmark

community held talks on how to improve the region’s power quality and reliability,

as well as how to reduce their dependency on fossil fuels and combat contributions

to global warming [2]. In August 2006, an application for federal government

funding was submitted to cover 50% of the project’s capital costs, with the balance

to be paid by private investors and loans [2]. Construction of the project began in

March 2012, with civil works completed in October 2012 [3]. The wind farm first

began generating on February 20th 2013 [3]. (Image used with author’s permission)

Figure 2: DCWF Construction

7

2.2 Denmark Community Windfarm Turbines

The wind farm currently comprises of two 800 kW ENERCON E-48, each of 55-

meter hub height and 48-meter blade diameter [4]. The WTGs are classified Class IV

variable speed, active pitch-controlled, inverter-coupled machines [4]. The

ENERCON SCADA system (ESS) installed in the WTGs allows for the remote

monitoring of generation and environmental parameters, logged in 10-minute

averages [4]. More information on the WTG characteristics can be found in

Appendix A: ENERCON E-48 WTG Specifications. (Image used with author’s

permission)

Figure 3: Anemomter at Mt Barker Wind Farm

8

2.3 Denmark Region Distribution Network

The South-West Interconnected System (SWIS), operated by Western Power, is the

medium of electricity transportation in the southwest of Australia. The transmission

network extends from Kalbarri in the north to Albany in the south and Busselton in

the west to Kalgoorlie in the east [5]. The Denmark distribution network forms part

of the SWIS. However, the remoteness of regional Western Australia means that

electrical power is generated in Albany and transmitted across 70km of transmission

lines to Denmark. Thus, the need for local generation becomes apparent.

The DCWF is connected to the SWIS at the terminating end of a 22km long 22kV

distribution line that branches out from the Lower Denmark Feeder (LDF). The LDF

is then connected to Albany Substation, which is approximately 70km along the

transmission line east of Denmark [6]. A simplified single line diagram of the

Denmark region distribution network is shown in Figure 4.

Figure 4: Simplified Denmark Region Distribution Network

9

2.4 Network Voltage Rise

Network stability and reliability is crucial in the continuous supply of electricity to

consumers. Sudden changes in generation or load demand in a network can cause

voltage rise or droop [7]. This may lead to switching events that effectively open

circuit the network, therefore causing a blackout.

As such, network voltage, frequency, and reactive power should all be monitored and

controlled within certain limits before network parameters fall outside operational

limits [8]. Western Power stipulates that generators connected to the SWIN must keep

network voltages within 0.9pu and 1.1pu, or ±10% of nominal voltage [8]. However, in

the planning stages of projects ±6% is used for voltage limits [7].

The DCWF is considered to be at a low fault level; the short circuit current

contributed by the WTGs is limited by the inverters, and the short circuit impedance

seen by the WTGs is greatest at the end of the LDF where the turbines are connected

[9]. The embedded generation source at the end of the high impedance LDF causes

significant voltage rise at the POC.

Limitations on the output of generators connected to distribution network may be

imposed to prevent this voltage rise [7]. To limit the voltage rise at the POC at the

DCWF, the wind farm is required to operate at 90% of rated capacity, 1.44MW (720

kW), and 0.9 lagging power factor, absorbing reactive power.

10

2.5 Battery Energy Storage Systems

A primary objective to ensure the reliability of any electrical power system is to

maintain a continuous balance between the production and consumption of

electrical power; power generated within the system must match the load demanded

by the system [9].

A considerable problem with renewable energy, such as wind and solar, is the

variability of resource supply. This variability makes it extremely difficult to match

renewable generators with real-time consumption, as the amount of electrical power

that is readily available fluctuates with resource availability, and the load demand

also changes with time of day, week and year [10]. A possible solution to this

problem is the storage of electrical energy so that it can be consumed on demand.

Battery storage allows electricity generated from renewable resources to be

consumed at peak network loads, rather than at times when network loads are low

and renewable generation is high [10]. Different factors have influenced the

commercialisation of battery storage technologies into the renewable energy market,

namely cost and product availability [11]. However, the technology, coupled with

renewable energy generators, is being progressively utilized in modern times as

research and development into the technology continues [11].

11

Battery energy storage systems (BESSs) have traditionally been very expensive in

utility-scale storage options. However, the price of such systems has declined in

recent years due to research and innovation, with studies predicting from that prices

will continue to decrease [12]. Research and development into various BESS

technologies has made several systems available for commercial utilisation, with

large-scale battery storage capacity now totalling more than 800 MWh worldwide

[13].

The price of BESSs are predicted to rapidly decline in years to come, which will also

see an increase in their implementation in renewable energy integration. Such

storage systems contribute to the security and reliability of wind power systems, as

the ability to store energy for later consumption is what is required to ensure load

demand will always be met. This will result in an increase in renewable energy

penetration [14].

13

3. WIND GENERATION ANALYSES

Assessment of a site’s wind resource and subsequent generation is one of the most

critical exercises in wind farm projects. This enables the wind farm operator to

evaluate the wind farm’s performance; troubleshoot switching events and outages;

and predict future wind farm generation to facilitate wind farm expansion.

A wind generation analysis of the DCWF in multiple operational states has been

undertaken in order to assess the optimal mode of operation. The optimal mode of

operation of the DCWF refers to the number of WTGs constituting the wind farm, as

well as the maximum power limit that will result in the greatest annual production

whilst minimizing cost and maintaining network stability.

The wind generation analyses conducted in this project have all used the same

methodology in order to provide an accurate comparison. This method is termed the

“ENERCON Power Curve” methodology. The analysis of the DCWF in its current

operational state has been studied using three separate analysis techniques. This is

done in order to verify that the “ENERCON Power Curve” methodology is accurate,

as the method is used extensively in subsequent parts of the project.

14

3.1 Data Used in Analysis

The analysis period that data has been obtained for the DCWF thesis project has

been chosen to be March 1st 2015 – March 1st 2016, providing one full year of data.

Using the annual period of March – March also provides two additional years of data

for comparison, as the DCWF has logged data since its commissioning in February

2013 [3]. Reliable weather station data is not available in the Denmark region, with

the closest wind speeds to correlate with measured in Albany, approximately 50 kms

away. The annual generation data obtained for the analysis period is 4.3% lower than

the average for all three years. Thus, the analyses presented in this report will be

slightly underestimated, but are adequate for comparison and assessment purposes.

The data acquired for this project has been obtained using the ENERCON SCADA

System (ESS). The ENERCON E-48 WTGs are remotely monitored using the ESS.

This provides the wind turbine operator the ability to download data that has been

logged by the WTGs [4]. Working with SkyFarming, the following data for each

WTG for the analysis period has been acquired:

• Average wind speed at hub height (m/s)

• Nacelle Orientation (°)

• Average power (kW)

• Average reactive power (kVAR)

• Energy produced (kWh)

15

The data has been downloaded for each month of the analysis period, provided in 10-

minute averages. Each 10-minute interval logged by the ESS has been averaged using

data logged every 1-2 seconds according to industry standards [15]. 51,196 data entries

were downloaded from the ESS, amounting to 1,364 data entries missing. Thus, the

data recovery rate is demonstrated by Equation 1.

𝐷𝑎𝑡𝑎 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒 =𝐷𝑎𝑡𝑎 𝑅𝑒𝑐𝑜𝑟𝑑𝑠 𝐶𝑜𝑙𝑙𝑒𝑐𝑡𝑒𝑑

𝐷𝑎𝑡𝑎 𝑅𝑒𝑐𝑜𝑟𝑑𝑠 𝑃𝑜𝑠𝑠𝑖𝑏𝑙𝑒×100

𝐷𝑎𝑡𝑎 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒 =51196

𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙𝑠𝑦𝑒𝑎𝑟

6𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙𝑠

ℎ𝑜𝑢𝑟×24

ℎ𝑜𝑢𝑟𝑠𝑑𝑎𝑦

×365𝑑𝑎𝑦𝑠𝑦𝑒𝑎𝑟

×100

𝐷𝑎𝑡𝑎 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒 = 97.4%

Equation 1: Data Recovery Rate of Downloaded Data

As only 2.6% of data is missing, the ENERCON SCADA logged data is acceptable to

use in the wind generation analysis of the DCWF according to the Wind Resource

Assessment Handbook [16]. Furthermore, the data was validated according to the

Wind Resource Assessment Handbook, with no suspect found. Additionally, the

yearly average wind speed for T1, 7.84 m/s, is similar to that of T2, 7.71 m/s. This

provides further evidence that the wind speed data logged by each WTG is accurate,

as the WTGs are in close proximity.

16

3.2 Generation Analysis – Two WTGs Restricted

A generation analysis of the DCWF in its current state of operation has been

performed in order to demonstrate the wind farm’s annual production with

currently imposed maximum power restrictions. As previously mentioned, the data

used in the analysis will be subsequently used in later parts of the project. Therefore,

it is vital that the generation analysis of the DCWF’s current operation be performed.

To ensure the accuracy of future results, the current generation analysis has been

undertaken using three independent methods; each will be compared to show the

data’s validity.

3.2.1 Method 1 - ENERCON SCADA System

The first generation analysis technique employed in the evaluation of the DCWF’s

current annual generation is the assessment of ENERCON SCADA data. As

mentioned beforehand, energy produced from each WTG has been downloaded via

the ESS. The energy produced by each WTG has been logged in kWh to one

significant figure for each month of the analysis period.

The annual output from each WTG has been found by summing all 10-minute

periods of energy production for each month of downloaded data.

17

3.2.2 Method 2 - ENERCON Power Curve

The second energy analysis method employed in the assessment of the DCWF’s

annual generation in its current operational state uses wind speed and the resulting

power produced by the WTGs. The power produced by the E-48 WTG at various

wind speeds is shown on the manufacturer’s datasheet [4]. The relationship is

represented in Table 25 in Appendix A: ENERCON E-48 WTG Specifications. A series

of equations have been developed in order to replicate the E-48 WTG power curve

shown in the manufacturer’s datasheet.

Wind speeds below 3 m/s produce no power from the WTG, and therefore this part

of the equation is defined as a constant 0 kW.

Wind speeds from cut-in wind speed, 3 m/s, to rated wind speed, 14 m/s, produce

variable power from the WTG. These wind speeds, obtained from the manufacturers

datasheet, have been plotted with their corresponding power produced, and then a

line of best fit applied to the plot. It is important to note that the line of best fit is

produced from a 6th order polynomial with the equation shown to 10 significant

figures in order to minimise errors. The generated equation is shown in Appendix A:

ENERCON E-48 WTG Specifications.

Wind speeds from 14 m/s to 28 m/s produce rated power from the WTG, 810 kW.

The relationship is modelled by a constant, 810 kW.

18

Assuming a linear ramp down relationship of the WTG for wind speeds between 28

m/s and 34 m/s, a further equation can be formulated that models the ENERCON

storm control feature. The storm control feature allows the WTG to reduce power

until cut-out wind speed is reached; therefore, the WTG does not suddenly stop

producing power. This linear ramp down relationship can be confirmed with visual

inspection of the power curve in the manufacturer’s datasheet [4].

Wind speeds above the WTG’s cut-out wind speed, 34 m/s, produce no power. The

relationship is modelled by a constant, 0 kW.

Table 1 shows the system of equations developed that estimate power produced by

the E-48 WTG for all wind speeds. Note that “x” represents wind speed. Additionally,

note that the system of equations shown in Table 1 is only shown to two decimal

places; the complete equation is shown in the developed equation in Appendix A.

Table 1: WTG Output Power Over Different Wind Speeds

Wind Speed Range (m/s) WTG Output Power (kW)

0-3 P = 0 3-14 P = 0.01x6 - 0.51x5 + 9.48x4 - 87.26x3 +

430.49x2 - 1060.64x + 1017.32 14-28 P = 810 28-34 P = -135x + 4590 >34 0

19

The WTG output power for all wind speeds is represented graphically in Figure 5

below. This has been achieved by plotting the equations shown in Table 1. The

formulated power curve is almost identical to the one shown on the manufacturer’s

datasheet.

Figure 5: ENERCON E-48 Formulated Power Curve

Annual generation for the analysis period can now be estimated using this series of

equations and wind speeds logged by the ESS. 10-minute averaged wind speeds for

both T1 and T2 have been downloaded from the system. The system of equations has

been implemented into Microsoft Excel using logic statements that test the logged

wind speed of each 10-minute interval.

0

100

200

300

400

500

600

700

800

900

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Po

we

r P

rod

uce

d (

kW)

Wind Speed (m/s)

ENERCON E-48 Formulated Power Curve

20

The result of the equations is the 10-minute average output power of T1 and T2. Each

10-minute period’s energy yield can then be found by multiplying the average WTG

output power by 1

6. An example of energy output for a 10-minute interval is shown

below in Equation 2, where the logged 10-minute average wind speed is 9.5 m/s.

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑂𝑢𝑡𝑝𝑢𝑡 𝑃𝑜𝑤𝑒𝑟 (𝑘𝑊) = 0.01x6 − 0.51x5 + 9.48x4 − 87.26x3 + 430.49x2 − 1060.64x + 1017.32

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑂𝑢𝑡𝑝𝑢𝑡 𝑃𝑜𝑤𝑒𝑟 (𝑘𝑊) = 0.01×9.56 − 0.51×9.55 + 9.48×9.54 − 87.26×9.53 + 430.49×9.52 − 1060.64×9.5 + 1017.32

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑂𝑢𝑡𝑝𝑢𝑡 𝑃𝑜𝑤𝑒𝑟 = 476.28 kW

𝐸𝑛𝑒𝑟𝑔𝑦 𝑃𝑟𝑜𝑑𝑢𝑐𝑒𝑑 = 𝑃𝑜𝑤𝑒𝑟×𝑇𝑖𝑚𝑒 = 476.28kW×10 minutes/hour

60 minutes/hour= 79.38𝑘𝑊ℎ

Equation 2: ENERCON Power Curve Method Example

The current operation of the DCWF restricts the operation of the two WTGs to 720

kW each. This control scheme was implemented into the “ENERCON Power Curve”

method using further logic statements in Microsoft Excel. This effectively allowed

the DCWF in its current state of operation to be modelled.

The annual generation from the DCWF for the analysis period was then found by

summing the energy yield for each 10-minute period for both T1 and T2.

21

3.2.3 Method 3 – Western Power Meter Data

The third and final energy analysis method used in the assessment of the DCWF in

its current state of restricted output is the study of the exported electricity meter

data. The utility operator, Western Power, logs all electricity exported from the

DCWF to the SWIS after all power quality and transformations have taken place.

This data is available to download from the Australian Energy Market Operator

(AEMO) website for each month of interest in 30-minute averages [17].

The annual generation for the DCWF using the “Western Power Logged Data”

method has been found by summing the logged generation from all months

downloaded for the analysis period.

3.2.4 Two WTGs Restricted Analysis Results

All three methods of analysis for the DCWF’s generation for the analysis period can

be summarised below. Figure 6 shows the monthly output from the DCWF

consisting of two WTGs restricted at 1.44 MW.

22

The “ENERCON SCADA System” method of analysis has resulted in 2,581 MWh

generated from T1 and 2,548 MWh generated from T2. The total generation from

two E-48 WTGs at the DCWF restricted at 1.44 MW for the year of analysis is

therefore 5,129 MWh.

The “ENERCON Power Curve” method of generation analysis for the DCWF has

resulted in 2522MWh produced from T1 and 2462 MWh produced from T2. The

annual generation for the wind farm for the analysis period is therefore equal to

4984 MWh.

The electricity generated from the DCWF using the “Western power Meter Data”

analysis has been found to be 5043MWh. Individual WTG generation data is not

available, as the export is logged by Western Power after the point of connection

(POC) of the wind farm.

The monthly generation from the DCWF for the analysis period from all three

analysis methods can be compared graphically in Figure 6. The graph shows that all

three analysis methods produce similar results and the overall trend is the same. The

generation from the “ENERCON SCADA System” method shows highest monthly

generation, and the “ENERCON Power Curve” method shows the lowest monthly

generation.

23

Figure 6: Comparison of Results from Analysis Methods

Table 2 provides a summary of the three generation analysis techniques used in the

assessment of the DCWF in its current operational state. The Table also shows the

percentage difference in annual generation between the ENERCON Power Curve

method, and other methods of analysis.

Table 2: Summary of Generation Analyses

Analysis Technique Annual Generation (MWh)

Percentage Difference

Monthly Average Generation (MWh)

ENERCON SCADA 5129 2.9% 427 ENERCON Power

Curve 4984 N/A 415

Western Power Meter

5036 1.0% 420

0.00

100.00

200.00

300.00

400.00

500.00

600.00En

erg

y Ex

po

rte

d (

MW

h)

Time (Month/Year)

DCWF Annual Generation - Two WTGs Limited

Enercon SCADA Enercon Power Curve AEMO Meter Data

24

The ‘ENERCON Power Curve” method demonstrates the least annual production

from the DCWF. This may be due to the anemometer that measures wind speeds for

the ESS being located behind the nacelle of the WTGs. However, most modern

WTGs take this shadow effect into consideration before logging wind speeds [18].

Further discrepancies may arise from the ESS accuracy. The system only logs energy

produced from the WTGs to the nearest whole number, which may overestimate the

actual energy yield from the DCWF.

Lastly, the meter data from Western Power is logged after the POC of the DCWF.

Thus, transformer losses and line losses have already occurred once the energy

produced from the WTGs has been logged. As both other methods of estimation

have not taken these losses into account, this may have resulted in increased

generation from the “Western Power Meter Data” analysis method.

However, the comparison of results in Table 2 shows that the difference between the

analysis techniques is relatively small. This confirms that the “ENERCON Power

Curve” method of analysis is accurate enough to use in further generation analyses of

the thesis project.

25

3.3 Generation Analysis – Two WTGs Unrestricted

The next generation analysis performed of the DCWF will assess the wind farm’s

annual generation with current constituents of two E-48 WTGs operating with no

restrictions. Current maximum output restrictions limit the DCWF to 90% capacity,

1.44 MW, in order to keep network voltages within acceptable limits. In order to

assess the impedance of the power restrictions on the DCWF, a generation analysis

has been performed with the wind farm operating at its full rated capacity of 1.6

MW.

The purpose of this analysis is to determine how much of the wind farm’s annual

generation is lost due to current maximum power restrictions. Assessment of the

wind farm’s annual loss of generation is used to determine whether the maximum

power limitation should attempt to be overcome.

3.3.1 Two WTGs Unrestricted Analysis Methodology

The generation analysis for the unrestricted operation of the DCWF has been

performed using the “ENERCON Power Curve” method. However, in this case the

turbines are not limited to 720 kW; instead, they are analysed operating with no

maximum power limit. This has been implemented into Microsoft Excel by removing

the limit to the energy production of each WTG that was previously imposed.

26

3.3.2 Two WTGs Unrestricted Analysis Results

The annual generation for the DCWF consisting of two WTGs with unrestricted

operation has been determined to be 5094 MWh. Compared to the annual

generation found for the analysis period using the same method, but with currently

imposed maximum power restrictions, an additional 110 MWh, or 2.2%, would be

achieved. This can be compared graphically in Figure 7.

Due to the impact of the DCWF on network voltage at the POC, the wind farm has

been limited to 90% of its capacity. In order to overcome this restriction, reactive

power compensators would need to be installed at the DCWF site, as will be

investigated further in this report. The difference in annual production between

limited and unlimited operation is very small for two WTGs; the implementation of

such reactive power elements would not be economically viable.

Figure 7: Two WTGs Limited and Unlimited Operation

4984 MWh

5094 MWh

0 1000 2000 3000 4000 5000 6000

Annual Production (MWh)

Two WTGs: Limited vs. Unlimited Operation

Unlimited - 1.6 MW

Limited - 1.44 MW

27

3.4 Generation Analysis – Three WTGs Restricted

The DCWF Board have specified that one option for expansion to the wind farm is

the inclusion of a third WTG. For ease of analysis, as well as maintenance

consistency and visual appeal of the wind farm, the additional WTG has been chosen

to be a third ENERCON E-48 WTG, Turbine 3 (T3). The operation of the third WTG

in both restricted and unrestricted operation has been analysed in order to

investigate all possible modes of operation of the DCWF.

If a third WTG is implemented at the DCWF, it may be possible that the wind farm

operates with a maximum power limitation for a limited period of time. This may

result due to a delay in raising the maximum power limitation of the wind farm.

This section of the report documents the generation analysis of the wind farm with

three WTGs restricted to 1.44 MW.

3.4.1 Three WTGs Restricted Analysis Methodology

The average of the wind speeds logged from the two existing WTGs has been used in

the analysis of the third WTG. This has been found to be the most suitable wind

speed available at the site. Logged wind speed data for the region has been found to

be very limited; this is discussed in detail in Project Complications.

.

28

The potential annual production from T3 has been estimated using the “ENERCON

Power Curve” method. The wind farm has been limited to 1.44 MW, with each WTG

limited to 480 kW. This is a very unlikely control scheme, as only 60% of the wind

farm capacity is utilised. However, as previously stated, this limitation would be

impermanent, and would only exist until the wind farm is operable at a greater

maximum power limit.

The implementation of this operational state has been performed using Microsoft

Excel. Due to the large amount of data used in the generation analysis, the results

can be viewed in the attached program.

3.4.2 Three WTGs Restricted Analysis Results

The generation analysis of the DCWF with three WTGs restricted to 1.44 MW

maximum output power has resulted in an additional annual generation of 1450

MWh, or 29.1%, compared to two WTGs restricted to the same limit. Thus, the total

annual generation with three WTGs restricted at 1.44 MW is 6436 MWh.

The result of this generation analysis shows that even if maximum power limits

cannot be overcome, it still may be economically feasible to implement a third WTG.

This will be investigated furthermore in Third WTG Economic Analysis.

29

3.5 Generation Analysis – Three WTGs Unrestricted

A generation analysis has also been performed of the expanded DCWF with three

WTGs operating with no maximum power restrictions. The purpose of this study is

to assess the potential annual generation of the DCWF after expansion and compare

this to other generation analyses. The developed model will also be used in

subsequent sections of the project.

3.5.1 Three WTGs Unrestricted Analysis Methodology

The method used in the analysis of three WTGs operating with no maximum power

limit is the same method used in previous analyses of the wind farm. The

“ENERCON Power Curve” methodology has been applied in order to attain

consistent results and provide an accurate comparison to other analyses.

3.5.2 Three WTGs Unrestricted Analysis Results

The generation analysis results of three WTGs operating with no maximum power

limitation are consistent with results obtained from previous analyses. The annual

generation from the expanded wind farm has been found to be 7639 MWh. This is

equal to 50% more than two WTGs operating unrestricted, as is expected.

30

The annual output from just T3 has been found to be 2545 MWh. Compared to when

the wind farm is operating at the current power limit of 1.44 MW, unrestricted

operation of T3 yields an additional 1203 MWh, or 18.7%, each year. This 18.7% is

therefore generation from T3 that would be lost if the maximum power of the DCWF

was limited to 1.44 MW.

The loss in annual production is substantially greater for three WTGs than the 2.2%

lost when only two restricted WTGs operate at the site. Thus, it becomes clear that

the maximum power limit of the wind farm becomes more consequential with the

addition of a third WTG. The full effect of increasing the maximum power limit on

the wind farm is discussed further in 3.6 Effect of Increasing Power Limitation.

The results from previous generation analyses are compared graphically in Figure 8.

Figure 8: Two and Three WTGs Limited and Unlimited Operation

4984 MWh

5094 MWh

6436 MWh

7639 MWh

0 2000 4000 6000 8000

Two and Three WTGs: Limited vs. Unlimited Operation

3 WTGs Limited - 2.4 MW


2 WTGs Unlimited - 1.6 MW


31

3.6 Effect of Increasing Power Limitation

A sensitivity analysis has been performed on how the annual generation of the

DCWF is affected by the increase in maximum power limit. The sensitivity analysis

begins at the current maximum power limit, 1.44 MW, and includes increasing

output limits of the wind farm up to the maximum capacity of three WTGs, 2.4 MW.

The results of the sensitivity analysis are shown below in Figure 9.

Figure 9: Sensitivity Analysis of Annual Generation with Increasing Power Limitation

The results from the sensitivity analysis show that increasing the maximum output

power of the wind farm results in more annual production. The trend appears very

linear from maximum power limits of 1.44 MW to 2 MW, and then starts to decay

much more rapidly. If the maximum power of the wind farm could only be raised to

a certain limit, 2 MW would result in significantly more annual generation.

6200.00

6400.00

6600.00

6800.00

7000.00

7200.00

7400.00

0 0.5 1 1.5 2 2.5 3

An

nu

al G

en

era

tio

n (

MW

h)

Power Limitation (MW)

Energy Yield with Increasing Power Limitation

32

3.7 DCWF Capacity Factor

The capacity factor is the ratio of the actual output of a generator over a period of

time to the maximum potential output of a generator over the same time period.

This is demonstrated by Equation 3. Represented by a percentage, capacity factor is a

measure of a wind farm’s performance and can vary significantly with location, wind

availability, wake losses, and maintenance [19]. The capacity factors for all system

options are shown in Table 3.

𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝐹𝑎𝑐𝑡𝑜𝑟 =

𝑂𝑢𝑡𝑝𝑢𝑡𝑌𝑒𝑎𝑟

𝑅𝑎𝑡𝑒𝑑 𝑂𝑢𝑡𝑝𝑢𝑡×24ℎ𝑜𝑢𝑟𝑠

𝑑𝑎𝑦×365

𝑑𝑎𝑦𝑠𝑦𝑒𝑎𝑟

×100

Equation 3: Capacity Factor

Table 3: Capacity Factors of Different System Options

Wind Farm Capacity Capacity Factor

2 WTGs – 1.44 MW 35.56% 2 WTGs – 1.6 MW 36.34%

3 WTGs – 1.44 MW 30.61% 3 WTGs – 2.4 MW 36.33%

As a comparison, the capacity factor for total wind generation in the United

Kingdom for 2015 was 33.7%, with this capacity factor being the highest on record for

19 years [20]. This confirms the DCWF site’s good wind resource and suitability for

the addition of a third WTG.

33

3.8 Third WTG Site

The placement of the third WTG at the DCWF site is important in order to optimise

its production and minimise its effect on the existing WTGs. T3 should not be placed

upstream of existing WTGs, as this would reduce the output of T1 and T2 [21]. In

addition, T3 should not be placed downstream of prevailing winds from T1 and T2, as

this would reduce its own output.

The yaw control of the WTGs positions the rotor to face the direction that the wind

is blowing [19]. In effect, the position of the nacelle will show the direction of

prevailing winds. Data downloaded from the ESS has provided the bearing of the

nacelle of T1 and T2 for the analysis period. Due to the amount of data downloaded,

this has not been included in the report but can be viewed in the attached Microsoft

Excel program.

34

A wind rose has been developed using the data downloaded from the ESS. Wind

speed data has been binned into eight bins to show the frequency of wind speeds in

each direction. The plot, shown in Figure 10, shows the relative frequency of wind

directions at the DCWF site. It is clear from the wind rose that the two prevailing

wind directions are from the Northeast and Southwest, with wind direction coming

from these directions more than 30% of the time. Thus, the third WTG should be

Northeast or Southwest of T1 or T2.

Figure 10: Wind Rose of the DCWF Site

Two possible sites have been selected for the implementation of T3 at the DCWF.

These sites, shown in Figure 11, represent where the additional WTG could be

located that would have minimal impact on the existing WTGs. Furthermore, the

0

2

4

6

8

10

12

14

16N

NE

E

SE

S

SW

W

NW

Wind Rose of the DCWF Site

35

sites have been chosen to limit the amount of land clearing required and electrical

cable used.

“Possible T3 Location #2” is shown to be North of T1 and Northwest of T2, and so

would possibly have the least effect on existing wind farm generation. “Possible T3

Location #1” is East of T2 and Southeast of T1, and so would have more influence on

the wind farm’s generation. However, “Possible T3 Location #1” is also slightly

elevated, and so would result in higher wind speeds and greater output from the

WTG. It must be noted, however, that a more detailed analysis would be required for

the optimal placement of T3, such as computer software like WAsP or Windfarm.

Figure 11: Possible Locations for T3

Possible T3 Location #1

Possible T3 Location #2

T1

T2

36

3.9 Third WTG Economic Analysis

The feasibility of a third WTG at the DCWF has been analysed using results from

generation analysis of three WTGs operating with and without maximum power

limits. The pricing of the third WTG has been estimated using a model developed by

Horizon Power. The price of has also been discussed with SkyFarming, who

managed construction of the existing WTGs.

The model developed by Horizon Power has estimated the installed price of a

generic onshore WTG to be $2,750/kWh, equating to $2.2m for the ENERCON E-48

WTG. Operation and maintenance (O&M) for the lifetime of the project was then

estimated at $40k/year, equating to $800k for the lifetime of the WTG. SkyFarming

provided an additional estimate for the third WTG of approximately $1.9m installed.

O&M has been assumed to be the same. Thus, the final price of the third WTG has

been calculated using the average of these two estimations, rounded up to $2.1m.

Additional costs from the implementation of the third WTG have been assumed to

be road construction costs and cabling and switchgear for the WTG. After liaising

with SkyFarming, this has been estimated to be $100k and $10k respectively. Please

note that no financial documentation for the original construction of the DCWF has

become available for this thesis project, complicating the economic analysis. A

breakdown of estimated expansion costs for the construction of the third WTG is

shown in Table 4.

37

Table 4: NPC of Third WTG Expansion

Component Cost

ENERCON E-48 WTG $2,100,000 O&M $800,000

Road Construction $100,000 Cabling and Switchgear $10,000

TOTAL $2,210,000

The revenue generated from the third WTG has been based on the economic model

devised in 4.4 BESS Economic Analysis. The wholesale price of electricity (POE) has

been taken to be $50/MWh; the price for large-scale generation certificates (LGCs)

has been taken to be $85/MWh; and the price for capacity credits has been assumed

to be $176,800/MW.

The payback period for a third WTG operating in restricted and unrestricted

operation is shown in Figure 12. The results from the economic analysis of the third

WTG expansion to the DCWF show that a third WTG would be economically

feasible. However, the variable price of the POE, LGCs, and capacity credits are

variable, and so the economic analysis of such a system is very approximate.

38

Figure 12: Third WTG Payback Period

A third WTG operating with no power restrictions would result in a payback period

of 4.8 years. The NPV of the additional WTG has been approximated to be $7.1m.

From the short payback period of the system and net revenue over the lifetime of the

project, a third WTG implemented at the DCWF operating at full capacity would be

a worthy investment.

A third WTG operating with a maximum power limit of 1.44 MW would result in a

payback period of 8.7 years. This system has a NPV of approximately $2.8m. Thus,

the implementation of a third WTG, even restricted to the wind farm’s current

power limit, is feasible.

-4

-2

0

2

4

6

8N

et

Re

ven

ue M

illio

ns

Year

Third WTG Payback Period

3 WTGs - Restricted 3 WTGs - Unrestricted

39

4. BESS ANALYSIS

One other option to consider in the expansion of the DCWF is the inclusion of

battery storage. The implementation of a BESS at the DCWF would facilitate the

addition of a third WTG as well as provide substantial benefits to the Denmark

distribution network. As such, the assumption has been made that the BESS will

only be considered with the implementation of a third WTG.

This section of the report will investigate several aspects that require consideration

with the implementation of a BESS. Suitable BESS technologies will be researched

and put forward, with two technologies ultimately considered. Different BESS sizes

will also be presented, with the objective to perform a generation analysis on the

expanded system.

With BESS type and size determined, specific BESS products can then be selected.

This study includes an in depth economic feasibility study of selected systems.

40

4.1 BESS Size

BESS size is divided into two components: battery power and battery capacity.

Battery power is the amount of power that a battery can deliver instantaneously [22].

Battery capacity is the amount of energy that can be stored in a battery [22]. These

two characteristics are governed by the design and chemistry of the battery [22], and

so it becomes apparent that BESS size will dictate the type of technology utilised.

The BESS power for the system to be implemented at the DCWF has been based

upon the required operation of the BESS. As the objective of the BESS is to

complement a third WTG at the DCWF, battery power has been selected to utilise

the full potential of three WTGs. Thus, the BESS must be capable of storing excess

energy when the DCWF is operating at rated output. A BESS power of 1 MW has

therefore been chosen for optimal utilisation, summarised below in Figure 13.

Figure 13: Battery Power Selection

3 WTGs Rated Power

2.4 MW

Maxium Power Limit

1.44 MW

Required Battery Power

0.96 MW

41

Battery capacity for the DCWF BESS has been selected using alternative methods.

The amount of storage required from the BESS is not determined by a load, but

rather by the amount of generation lost due to the maximum power limitation.

Using the previously developed generation analysis model, the annual output from

the DCWF with battery storage has been estimated. This model will be discussed in

detail in 4.3 BESS Generation Analysis. The annual output from just the BESS with

increasing battery capacity is shown below in Figure 14. From this plot, a BESS

capacity of 4 MWh has been chosen to optimise the output from the BESS whilst

minimising the size, and hence cost, of the BESS.

Figure 14: Annual Output of BESS with Inreasing Battery Capacity

0

100

200

300

400

500

600

700

800

0 2 4 6 8 10 12

An

nu

al P

rod

uct

ion

(M

Wh

)

Battery Capacity (MWh)

Additional Output from Battery Energy Storage System

42

4.2 BESS Type

Various battery technologies are currently available for commercial utilisation, with

the battery’s characteristics governed by the technology utilised. Thus, some

technologies are recommended more for large-scale storage than others. Important

battery characteristics to consider for utility-scale integration include:

• Cost;

• Lifetime;

• Round trip efficiency;

• Depth of discharge;

• Energy Density; and

• Maintenance.

Two battery technologies have been investigated for possible implementation at the

DCWF based on their optimal characteristics for use in large-scale systems:

Vanadium Redox batteries (VRBs) and Lithium-Ion batteries (LIBs).

43

4.2.1 Vanadium Redox Battery Option

VRBs, also known as flow batteries, are a type of battery storage cell comprising of

two solutions of Vanadium in different valence states. The two solutions are kept in

separate storage tanks and then pumped across an ion-exchange membrane.

Electrons flow across the membrane from the catholytic solution to the analytic

solution as a chemical reaction occurs, producing a DC current. This chemical

reaction is represented in Equation 4 below [23]. A visual representation of the VRB

technology is shown in Figure 15 [23].

𝑉𝑂2+ + 2𝐻2 ⟶ 𝑉𝑂2+ + 𝐻2𝑂 − 𝑒− (Positive Electrode)

𝑉3+ + 𝑒− ⟶ 𝑉2+ (Negative Electrode)

Equation 4: Vanadium Redox Chemical Reaction

VRB technology has some significant benefits as a utility-scale BESS in comparison

to other battery technologies. A summary of VRB benefits are listed in Table 5. The

technology has been implemented in similar projects to the proposed expansion of

the DCWF, such as on the Huxley Hill Wind Farm on King Island, Tasmania [24].

44

Figure 15: Vanadium Redox Battery Technology

Table 5: Utility-Scale Vanadium Redox Battery Advantages

Battery Property Advantage

Battery capacity is proportional to tank size [22]

Cheaper $/kWh - lower cost for large-scale systems

Short response time [25] Can be discharged very quickly (ms) Efficiency does not degrade

over battery lifetime [22] Greater energy yield over longer project lifetimes

Capable of 100% DoD [26] All battery capacity can be utilised Electrolyte lasts indefinitely [22] Long system lifetime Can be mechanically recharged

with electrolyte replacement [22] Battery can be recharged

very quickly Low self-discharge [27] Stored longer with no loss in capacity

The VRB technology also has some disadvantages associated with its use in large-

scale systems. These are summarised in Table 6.

https://www.google.com.au/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwi4zcbZ36TRAhUEmZQKHfrvC5kQjRwIBw&url=http://large.stanford.edu/courses/2011/ph240/xie2/&psig=AFQjCNEU5sme0HgXiBSZik7kF7OVFACqHA&ust=1483490315489264

45

Table 6: Utility-Scale Vanadium Redox Battery Disadvantages

Battery Property Disadvantage

Low round-trip efficiency (65%-85%) [12]

Higher system losses resulting in lower energy yield

Low energy density [22] BESS requires more area Requires pump for electrolyte

and cooling for battery [28] Consumes power to operate

A particular VRB suitable for utilisation at the DCWF is the Gildemeister CellCube

250-1000. Gildemeister is a reputable battery manufacturer that specialises in VRB

technology. The product can be provided and installed by VSUN, a Perth-based

company that provides on and off grid renewable energy solutions.

The CellCube 250-1000 is available in modular units, and so the BESS is scalable in

units of 250 kW. Thus, four units would be required for the DCWF project, with the

final system having a rated power of 1 MW and a storage capacity 4 MWh.

As the units are manufactured in prefabricated containers, the transportation,

installation, and commissioning of the BESS is not complicated and capital

expenditure is reduced. The BESS is also provided with shelter from environmental

extremes.

The technical specifications for the CellCube 250-1000 are can be viewed in Table 7

[26]. Specifications shown are for the complete BESS to be implemented at the

DCWF.

46

Table 7: Gildemeister CellCube 250-1000 Specifications

Battery Characteristic Value

Rated Power (AC) 1 MW Maximum Power (AC) 1.2 MW

Maximum Reactive Power ±1 MVAr Rated Energy Capacity (AC) 4 MWh (rated power, continuous) Total Energy Capacity (AC) 4.8 MWh (50% rated power, continuous) Roundtrip Efficiency (AC) 65% Design and Service Life 20,000 cycles > 20 years Output Voltage Options 400V/480V

Standard Operating Conditions (Outdoors) -15°C - +50°C Foot Print (Includes Staircase) 320m2

Gross Weight (Battery Full) 560 T

4.2.2 Lithium-Ion Battery Option

LIBs have traditionally been used in small, portable devices. However, continued

research and development has seen the battery technology used in large-scale

systems. LIBs operate from Lithium ions moving between the battery’s electrodes

through an electrolyte. The Lithium ion’s valence electron then follows an external

circuit between the electrodes maintaining electrical potential [29]. This process is

demonstrated graphically in [30].

47

Figure 16: Lithium-Ion Battery Technology

LIB technology is currently being utilised in many large-scale projects in Australia,

with 3.75 MWh of storage capacity currently operational across five projects as of

2015 [12]. The technology has significant advantages in utility-scale storage,

summarised in Table 8. Disadvantages of the technology are presented in Table 9.

Table 8: Utility-Scale Lithium-Ion Battery Advantages

Battery Property Advantage

High round-trip efficiency (85%-98%) [29]

Lower system losses resulting in higher energy yield

Short response time [12] Can be discharged very quickly (ms) High energy density [12] More compact BESS Low self-discharge [12] Stored longer with no loss in capacity

Long cycle life [29] Long system lifetime Capable of 100% DoD [26] All battery capacity can be utilised

48

Table 9: Utility-Scale Lithium-Ion Battery Disadvantages

Battery Property Disadvantage

Thermal runaway [31] Unsafe without appropriate control Efficiency degradation over

cycle life [31] Gradual loss in energy yield

over project lifetime

The model of LIB chosen to be suitable for implementation at the DCWF is the Tesla

Powerpack 2.0. The mass production of the LIB has made the technology much more

competitive. The BESS can also be supplied and installed by Tesla, a company with a

great deal of experience in large-scale LIB integration. The technical specifications

for the BESS are shown in Table 10.

The Powerpack 2.0 units, like the VRB also investigated, are modular in design. The

batteries come in self-containing enclosures and so do not require additional shelter.

Table 10: Tesla Powerpack 2.0 Specifications

Battery Characteristic Value

Rated Power (AC) 1 MW Maximum Power (AC) 1.2 MW

Maximum Reactive Power ±1 MVAr Rated Energy Capacity (AC) 4.2 MWh Roundtrip Efficiency (AC) 85% Design and Service Life 10 years Output Voltage Options 400V/480V

Standard Operating Conditions (Outdoors) -35°C - +50°C Foot Print (Includes Staircase) 77m2

Gross Weight (Battery Full) 181 T

49

The efficiency of the LIB BESS is shown to be much greater than the VRB, which

would result in more annual production. The efficiency of the VRB suggests that the

BESS is not ideal for short term energy storage, but rather for time-shifting large

intervals of generation. Additionally, the footprint of the LIB BESS is much less than

that of the VRB BESS, which may be advantageous, as this would reduce the

additional land needed to be cleared on the DCWF site.

The LIB BESS lifetime, however, means that the system will need replacing halfway

through the project life. The VRB does not require replacing during the project

lifetime, and may not require replacing even after the lifetime of the project.

Both BESS options are operational in outside temperatures up to 50°C. The

maximum recorded temperature for the region, recorded at Albany airport

approximately 50 km away, is 40.6°C [32].

50

4.3 BESS Generation Analysis

There are a number of ways to operate a BESS at the DCWF depending on the

primary objective of the wind farm. The BESS can be operated to benefit the wind

farm operator, Denmark Community Windfarm Pty Ltd; the utility operator,

Western Power; or a combination of these depending on the time of year.

Additionally, the BESS can be operated to support a microgrid in the Denmark

region. This would reduce the Denmark region’s dependency on electricity

generated from fossil fuel sources. However, this mode of operation requires analysis

of load data for the Denmark region which has not become available for this project.

Thus, two modes of BESS operation will be investigated in the expansion of the

DCFW: Maximum Generation Mode (MGM) and Peak Shaving Mode (PSM).

4.3.1 Maximum Generation Mode

The first mode of operation that the expanded DCWF could utilise would maximise

the output from the wind farm. This would benefit Denmark Community Windfarm

Pty Ltd the most financially with the current power purchase agreement (PPA). The

current PPA stipulates that generation from the DCWF is sold at a set price

regardless of time of day or year.

51

In MGM, the DCWF would be able to store the excess generation from the WTGs in

the BESS when the wind farm is operating above its maximum power limit, 1.44 MW.

The BESS could then export the stored electricity when the wind farm is operating

below its maximum power limit. Thus, the BESS would aim to keep the output of the

DCWF at its maximum output limit. MGM assumes that the maximum output limit

for the DCWF will remain capped.

A BESS generation analysis with the BESS in MGM has been performed using

Microsoft Excel. The model previously used to analyse the generation from three

WTGs has been further developed in order to accommodate for the BESS. The BESS

control logic used to implement MGM into Microsoft Excel is shown below in Table

11. Each statement is in order of precedence.

Table 11: Maximum Generation Mode Control Logic

IF THEN

Output > Maximum Limit Import (Output – Maximum Limit) into Battery

Energy in Battery > Battery Capacity Energy in Battery = Battery Capacity (Output < Maximum Limit) AND (Energy in Battery - (Maximum Limit – Output) > (1 -

Maximum DoD))

Export ((Maximum Limit – Output) * Battery Efficiency) from Battery

Energy in Battery - (Maximum Limit – Output) < (1 - Maximum DoD)

Export (Energy in Battery * Battery Efficiency) from Battery

AND Energy in Battery = Maximum DoD

52

Where:

Output = Unrestricted output from Three WTGs Maximum Limit = DCWF maximum output limit Energy in Battery = Energy stored in BESS Battery Capacity = Maximum energy that can be stored in BESS Maximum DoD = Maximum allowed depth of discharge for BESS Battery Efficiency = Round-trip efficiency of the BESS

The total output from the expanded DCWF can then be found by summing the

generation from three WTGs restricted to 1.44 MW and the generation from the

BESS.

The MGM model has been developed so that the wind farm maximum output limit,

and BESS capacity and DoD can be changed. This allows the CellCube and

Powerpack BESSs to be simulated based on their individual technical specifications.

The results are shown in Table 12.

Table 12: BESS Energy Flow Simulation Results – Maximum Generation Mode

BESS Specification VRB LIB

Maximum Limit 1.44 MW 1.44 MW Battery Capacity 4 MWh 4.2 MWh

Depth of Discharge 100% 100% Battery Efficiency 65% 85%

Annual Energy Exported (Battery) 309 MWh 413 MWh Annual Energy Exported (DCWF) 6743 MWh 6861 MWh Increase in Annual Generation

(Compared to 3 WTGs restricted with no BESS)

4.81%

6.43%

53

4.3.2 DCWF Output with BESS in MGM

In order to demonstrate the output of the DCWF composed of different system

options, various graphs have been plot. The graphs show how the implementation of

the BESS in MGM can help maintain the wind farm at its maximum output.

A plot of the best week of generation during the analysis period is shown in Figure

17. The plot shows two WTGs reaching the maximum output of 1.44 MW frequently

and three WTGs reaching the maximum output most of the time. Three WTGs with

battery storage provides almost a constant output of 1.44 MW.

Figure 17: DCWF Best Week of Generation

0.00

50.00

100.00

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DC

WF

Ou

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Best Week of Generation

Total Energy Produced (3 WTGs Unlimited) Total Energy Produced (3 WTGs + B)

Total Energy Produced (3 WTGs Limited) Total Energy Produced (2 WTGs Limited)

54

Figure 18 shows the output of the DCWF during the worst week of generation in the

analysis period. The plot shows that the output from two WTGs reaches the

maximum limit of the wind farm only once or twice towards the end of the week.

The output from three WTGs reaches the maximum limit more frequently at the end

of the week, but not enough to charge the battery. This is apparent from the

fluctuating output from the wind farm; generation cannot be kept constant as there

is no energy in the BESS to do so.

Figure 18: DCWF Worst Week of Generation

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Ou

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Worst Week of Generation



55

The output of the DCWF during an average week of generation is shown in Figure

19. The most average weekly yield from the wind farm during the analysis period has

been found through the analysis of the yearly data’s average and standard deviation.

The plot shows the output from two WTGs reaching the maximum limit of the wind

farm quite frequently. Three WTGs shows a higher output from the wind farm, and

the maximum output is reached more frequently.

The implementation of the BESS shows how the potential of three WTGs can be

utilised to maximise the generation from the DCWF, even when the wind farm is

restricted in its operation.

Figure 19: DCWF Average Week of Generation

0.00

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WF

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56

4.3.3 Peak Shaving Mode

The second mode of operation that the expanded DCWF could utilise is using the

BESS as a peak shaving device. In PSM, energy could be stored in the battery from

the WTGs during times of base load. The battery could then export this energy

during times of peak load. Using the battery in PSM would benefit the utility

operator the most, as this would substantially reduce the load on the LDF during

peak times.

Operation of the BESS in PSM could also benefit the DCWF financially if the wind

farm could arbitrage between on-peak and off-peak times. Furthermore, the

guarantee of output during peak demand would attract additional capacity credits.

However, this would require a new PPA, and so the financial benefits of operating

the BESS in PSM will not be investigated in this report.

A BESS generation analysis has been performed with the BESS operated in PSM. The

control logic used to implement the BESS PSM into the existing Microsoft Excel

model is shown in Table 13.

57

Table 13: Peak Shaving Mode Control Logic

IF THEN

Time = Off Peak Import Output into Battery Energy in Battery > Battery Capacity Energy in Battery = Battery Capacity

Time = On Peak AND Output > Maximum Limit

Export 0 from Battery

Time = On Peak AND Output < Maximum Limit AND (Energy in Battery - (Maximum

Limit – Output) > (1 - Maximum DoD))

Export (Maximum Limit – Output) * Battery Efficiency) from Battery

Time = On Peak AND Output < Maximum Limit AND (Energy in Battery - (Maximum

Limit – Output) < (1 - Maximum DoD))

Export (Energy in Battery * Battery Efficiency) from Battery

AND Energy in Battery = Maximum DoD

Where:

Time = Time of ten-minute interval tested Off Peak = Off-peak period1 On Peak = On-peak period2 Output = Unrestricted output from three WTGs Maximum Limit = DCWF maximum output limit Energy in Battery = Energy stored in BESS Battery Capacity = Maximum energy that can be stored in BESS

1 Off peak period defined as 21:00 to 15:00 [41] 2 On peak period defined as 15:00 to 21:00 [41]

58

Table 14: BESS Energy Flow Simulation Results – Peak Shaving Mode

BESS Specification VRB LIB

Maximum Limit 1.44 MW 1.44 MW Battery Capacity 4 MWh 4.2 MWh

Depth of Discharge 100% 100% Battery Efficiency 65% 85%

Annual Energy Exported (Battery) 585 MWh 787 MWh Annual Energy Exported (DCWF) 6487MWh 6494 MWh Percentage Increase in Annual Production (Compared with 3 WTGs restricted and no BESS)

0.83%

0.94%

Results from the simulation of the BESS in PSM show that although the BESS

contributes more to the DCWF’s annual production, the actual annual generation

from the DCWF is substantially lower than when the BESS is operated in MGM. The

BESS is cycled more deeply, but the energy flow of the system is mostly balanced;

the BESS imports generation off-peak, and the same generation is then exported on-

peak.

Effectively, the BESS provides a time-shift for generation to be consumed at peak

loads when operated in PSM. As previously mentioned, this may still benefit the

DCWF financially if a new PPA were arranged. However, additional financial

information would be required in order to assess the economic feasibility of the

BESS in PSM.

59

4.4 BESS Economic Analysis

Battery economics are changing very rapidly in today’s market due to their

increasing demand in home storage, electric vehicles, and renewable integration

[33]. Research and development, as well as mass production into battery storage

technologies have seen the price of BESSs decline in recent years [34], with prices

predicted to continue to decline. AECOM predicts that LIB prices will fall from $550

USD/kWh in 2014 to $200 USD/kWh in 2020 (64% reduction) [12]. Additionally, VRB

prices are predicted to fall from $680 USD/kWh in 2014 to $350 USD/kWh in 2020

(51% reduction) [12].

As the international market for BESSs continues to change, it is quite difficult to

provide accurate and reliable pricing for such systems. Effectively, prices given in

this report should be taken only as an approximate guide, with the figures presented

subject to change in years to come.

4.4.1 BESS Pricing

Quotations for both BESSs have been obtained from VSUN and Tesla, with the

prices as follows.

60

Tesla has quoted that the total price of the proposed LIB BESS system would amount

to approximately $3.1m – $3.4m AUD, and an additional $150k for transportation and

installation of the BESS. The average price of the quotation has been applied for the

purpose of this project, and so the final installed price for the LIB BESS is $3.4m.

The LIB BESS has a design life of 10 years, meaning that the battery will require

replacing halfway through the project lifetime. A discount rate of 8% and inflation

rate of 2% has been applied to the replacement cost of the BESS. A 30% reduction

has also been applied to the replacement system, reflecting falling battery prices [35].

Thus, the replacement LIB BESS has been estimated to be $1.27m.

VSUN has quoted that each CellCube 250-1000 unit would amount to approximately

$1.3m AUD. As four units are required, this would equate to $5.2m AUD. However, it

has been suggested that the purchase of multiple units would discount this price. A

discount of 15% has therefore been applied to the original quoted price. Using the

same shipping and installation price as the LIB BESS, the final installed price for the

VRB BESS is $4.57m.

Additional costs for the BESS expansion to the DCWF have also been taken into

consideration. A 400 V/22 kV transformer is necessary for the BESS. This has been

estimated to be $50k installed, after a quotation from Excess Power Equipment.

61

A net present balance of system cost for the 20-year lifetime of the BESS expansion

project is shown in Table 15.

Table 15: NPC of BESS Expansion

Component Cost

BESS

VRB LIB $4,570,000 $3,250,000 (Initial)

$1,270,000 (Replacement)

BESS Installation $150,000 $150,000 (Initial) $84,000 (Replacement)

Battery Transformer $50,000 Cabling and Switchgear $10,000

TOTAL

VRB LIB $4,780,000 $4,814,000

4.4.2 BESS Payback

The payback analysis of the proposed BESS expansion to the DCWF is conditional to

many economic elements – capital costs, revenue, and loan interest to name a few.

The NPC of the proposed expansion options has been determined in BESS Pricing.

Loan interest from borrowed finance for the proposed expansion is beyond the scope

of this project, and so will not be covered in detail. However, revenue from the

expanded wind farm will be investigated in order to determine the NPV and simple

payback of the system.

62

Revenue for the DCWF will include generation sales, Renewable Energy Certificates

(RECs), capacity credits, and government grants.

The revenue received by the DCWF for the sale of generated electricity is conditional

to the PPA between the wind farm and Synergy. Due to confidentiality reasons, the

wholesale price that the DCWF sells electricity for is not available. The price has

therefore been approximated from AEMO data. AEMO has stated that the average

Short Term Energy Market (STEM) price for the period 2016–2017 to be $50.09/MWh

[36]. Thus, $50/MWh will be used for the price of wholesale electricity in the

economic analysis of the proposed expansion to the DCWF.

The price of wholesale electricity is predicted to increase in coming years. A study

for AEMO by Jacobs predicts that the price of wholesale electricity will rise by 80%

throughout the 20-year lifetime of the project [37]. Consequently, a 3% increase in

the price of electricity has been factored into the proceeding analysis.

RECs, in the form of Large-scale Generation Certificates (LGCs), are a source of

revenue for energy wholesalers that generate electricity from renewable resources.

Each LGC is equivalent to 1 MWh. The current price of LGCs is $87.50 [38], with the

average price for the period of April 2016-December 2016 being approximately $85

[39]. The price of $85 for RECs will be used in the economic analysis of this report.

63

Capacity credits are purchased in the Wholesale Electricity Market (WEM) by

market customers to ensure that peak load demand can be met. The amount of

capacity credits that a generator receives is based on the generator’s forecast

contribution to peak demand [40]. The DCWF currently receives 1.118 MW of

capacity credits for the interval of 2016-2017 [40]. The Benchmark Reserve Capacity

Price (BRCP) is stated by AEMO to be $176,800 per MW per year for the 2016-2017

period. The capacity credits generated from the addition of the BESS has been

calculated based on the contribution of the BESS generation to total generation.

Government grants may also become available to the DCWF to help fund the BESS

expansion. Due to the inclusion of utility-scale battery storage, the DCWF could

apply for further funding from the Australian Renewable Energy Agency (ARENA).

However, this is beyond the scope of this project, and so has not been included in

the economic analysis.

A breakdown of all revenue that the DCWF may be entitled to is shown in Table 16.

For the purpose of the model, the BESS will be operated in PSM.

64

Table 16: DCWF Revenue with Third WTG and BESS

BESS Type Revenue Type Approximate Revenue

LIB

Electricity Generation

$50/MWh 413 MWh/year $20,650/year

RECs


Capacity Credits $176,800/MW 0.93MW/year $164,424/year

VRB

Electricity Generation


RECs


Capacity Credits

$176,800/MW 0.69MW/year $121,992/year

The payback period for the BESS expansion to the DCWF has been calculated to be

longer than the lifetime of the project. This is shown graphically in Figure 20. The

net present value plots do not cross the break-even mark for either BESS. Thus, if

either BESS option were implemented in 2017, the project would not be

economically feasible.

65

Figure 20: Payback Period for BESS Expansion in 2017

The varying price of wholesale electricity, LGCs, and capacity credits has made it

difficult to determine whether the implementation of the proposed BESS expansion

at a future date will be economically feasible or not. Figure 21 shows the payback

period of the same BESS expansion options if they were implemented in 2020.

The prices of both systems have been reduced by 30%, as predicted by the

International Renewable Energy Agency [35]. However, the LIB replacement has

been kept at $1.27m as per the previous model. In addition to this, the LGC price has

been increased to $100/MWh and capacity credits have been increased to $190,000.

The POE has been left as previously modelled, rising 3% each year.

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66

Figure 21: Payback Period for BESS Expansion in 2020

The payback period for the proposed BESS expansion options shown in Figure 21

demonstrates that both systems will pay themselves off before the end of the project

lifetime. The LIB option, although has a greater NPC, has a shorter payback period of

approximately 14 years. The NPV of the LIB is also greater at $1.52m. The VRB BESS

has a payback period of approximately 17 years, and a NPV of approximately $0.64m.

The results from the economic analysis show that it is not currently viable to

implement either of the proposed BESS expansion options at the DCWF. However,

the results also show that it may be a better option to implement the BESS in the

near future. This could be done after the installation of the third WTG. Another

option would be to install the BESS in stages; this is possible due to the system’s

modular design.

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67

5. OVERCOMING RESTRICTIVE POWER LIMITATIONS

5.1 BESS Inverter

The first option that could be employed in the overcoming of the maximum power

limit of the DCWF is the utilisation of the BESS. Both BESS options presented are

installed with inverters capable of reactive power injection or absorption.

Furthermore, they are able to operate at any power factor from 0 to 1, and so have

much more control over voltage at the POC than the WTG inverters. This would

allow the WTGs to operate at full capacity whilst the BESS absorbs reactive power,

limiting the rise in voltage.

However, utility-scale BESSs have been investigated and established to be too

expensive for implementation at the DCWF with the current market price. The

economics of such a system have not been modelled with full output from the wind

farm, though, due to time constraints within the project. This may be a concept for

scope of future works.

5.2 STATCOM

Implementation of a separate STATCOM at the DCWF was originally considered as

an option to overcome the maximum power limit of the wind farm. However, an

integrated STATCOM option is now available, which will be investigated further.

68

5.3 ENERCON WTG Technology

One other option that will be investigated to overcome the DCWF’s maximum

power limitation is the implementation of the third WTG with alternative

technology. The current WTGs at the DCWF are capable of reactive power injection

and absorption at 0.9 power factor. This would produce a reactive power capability

of up to ±387.46 kVAr. This reactive power is only available from the WTG when

there is active power generation. This is represented by Figure 22 [41].

Figure 22: Conventional E-48 WTG P-Q Characterisitc

69

ENERCON WTGs are also capable of installation with more reactive power control

capability. This is known as the Q+ option. The Q+ option allows the WTG to

operate at up to a power factor of 0.8 leading/lagging. This reactive power injection

or absorption from the WTG is then increased to ±600 kVAr. This would allow the

WTG to absorb more reactive power at times of high active power generation

without having adverse effects on system voltage. However, the WTG still needs to

generate active power in order to inject or absorb reactive power. This is represented

in Figure 23 [41].

Figure 23: E-48 WTG with Q+ P-Q Characteristic

Another option for the DCWF to consider is implementation of the third WTG with

the STATCOM option. This would allow the installation of the third WTG with a

70

dedicated STATCOM. The STATCOM would allow the WTG to have dynamic

control over the voltage at the POC. The option would allow the WTG to inject or

absorb reactive power even with no active power generation. ±600 kVAr is still the

maximum reactive power available; however, this is now available with no active

power generation. This is demonstrated in Figure 24 [41].

During times of no wind and no wind farm output, the WTG could inject reactive

power. This would raise the voltage at the POC. During times of where the wind

farm is operating at rated power, the WTG could absorb reactive power. This would

lower the voltage at the POC. Effectively, the voltage swing between no output and

maximum output is much less. Therefore, the wind farm may be able to operate at

rated power whilst keeping the network voltages within acceptable limits.

Figure 24: WTG with Q+ and STATCOM P-Q Characteristic

71

6. SIMULATION OF NETWORK VOLTAGES

The embedded generation source at the end of the LDF has been shown to cause

network voltage to rise beyond stipulated limits. As a result, the maximum output of

each WTG is limited so that this voltage rise at the POC is always held within

acceptable limits. Careful consideration must be taken to ensure wind farm

generation is maximized whilst keeping the distribution network stable.

In order to accurately assess the impact that the different DCWF expansion options

have on the Denmark distribution network, simulations of the different system

options have been carried out with the voltage at the DCWF’s POC studied.

A model of the original and expanded wind farm has been developed in DIgSILENT

PowerFactory, and simulations have been carried out to investigate network issues

and performance. Studies of distribution networks typically consider +6% and -10%

the operational limits for bus voltage [7]. For the purpose of this study, +7% has been

considered due to the simplified nature of the model.

Different expansion options simulated include two WTGs in limited and unlimited

operation; three WTGs in limited and unlimited operation; three WTGs with Q+ in

limited and unlimited operation; and 3 WTGS with Q+ and STATCOM in limited

and unlimited range.

72

6.1 PowerFactory Model

The network model simulated in PowerFactory has been developed using simplified

analysis methods and lumped parameters due to the limited information available

on the Denmark distribution network. This simplified network simulated in

PowerFactory is shown in Figure 25.

Albany Substation is modelled as an “External Grid” generation source. Albany and

Denmark are both represented as buses, the transmission line connecting the two

buses representative of the LDF. The LDF ends at the POC. The load seen by the

DCWF is modelled as an active and reactive load at the Denmark Bus. Capacitor

banks present along the LDF are modelled as a lumped shunt capacitance at the

Denmark Bus. The WTGs are connected to the POC via a transmission line that

models the equivalent 250m line impedance from each WTG. Table 26 in Appendix

B shows the value of the network parameters.

Figure 25: PowerFactory Simulated Network

73

6.2 Simulation of Original Network

Figure 26 shows the PowerFactory simulation of the original Denmark region

distribution network prior to the DCWF connection. The purpose of this simulation

is to provide a base case so that other simulated scenarios may be tested for voltage

swing. Additionally, the simulation of the original distribution network allowed the

model to be correctly developed.

As the load profile of the region has not become available for the project, model

component values were iterated until certain criteria were met. Previous studies of

the DCWF distribution network stated that the LDF was at its current capacity prior

to the connection of the DCWF, with the application of the -10% voltage limit

regulation [41]. Effectively, this means the voltage at the POC is maintained at 0.9 pu

prior to the DCWF being connected. Thus, the Denmark Load and Capacitor Bank

were modelled as lumped components at the POC and varied until:

• The voltage at the POC was equal to 0.9 pu;

• The power factor at the source was 0.993 leading; and

• The power factor was maintained at 0.9 lagging whilst maintaining the

Denmark Load

as per Western Power’s previous findings [41].

74

Figure 26: Simulation of Original Network

Table 17 shows the results of interest from the simulation of the original Denmark

distribution system. The voltage at the POC is shown to be 0.9, as per the criteria

from previous studies. The load at the Denmark Bus is 2 + 0.97j MW (pf 0.9

absorbing).

Table 17: Simulation of Original Network Results

DCWF Output – P DCWF Output – Q Voltage at POC ΔV (%)

0 MW 0 MVAr 0.899 pu N/A

75

6.3 Simulation of Two WTGs – Limited Output

Figure 27 shows the simulated LDF network with the DCWF connected. The DCWF

consists of two WTGs and the power generated has been limited to 1.44 MW in this

case, the current maximum output of the wind farm. Previous studies have found

that the wind farm is borderline operational whilst limited to 90% of its rated power

and operating at 0.9 absorbing power factor [41]. The borderline condition entails

that a 6% voltage rise would occur when the wind farm is operating at 1.44 MW.

Figure 27: Simulation of Two WTGs - Limited Output

The result from the simulation, shown in Table 18, show that a 7.23% rise in voltage

occurs at the POC when the DCWF is connected. This is slightly higher than the 6%

allowable limit; however, the slight inconsistency has been attributed to the

simplified nature of the model.

Table 18: Simulation Results of Two WTGs - Limited Output

DCWF Output – P DCWF Output – Q Voltage at POC ΔV

1.44 MW -0.70 MVAr 0.965 pu 7.23%

76

6.4 Simulation of Two WTGs – Maximum Output

The PowerFactory simulation shown in Figure 28 shows a simulation of the

Denmark distribution system with the DCWF consisting of the two existing WTGs

operating at their potential maximum output, 1.6 MW. The results from the

simulation are shown in Table 19.

Figure 28: Simulation of Two WTGs – Maximum Output

The results show that a 7.79% rise in voltage occurs at the POC, which is higher than

when the wind farm is limited to 1.44 MW. This is consistent with previous findings

that the voltage at the POC is outside allowable limits when the DCWF is operating

at its potential maximum output.

Table 19: Simulation Results of Two WTGs – Maximum Output

DCWF Output - P DCWF Output - Q Voltage at POC ΔV

1.6 MW -0.78 MVAr 0.970 pu 7.79%

77

6.5 Simulation of Three WTGs – Limited Output

Figure 30 shows a simulation of the Denmark distribution system with the expanded

DCWF inclusive of three WTGs connected. The WTGs have been limited to 1.44

MW, equally capped at 0.48 MW. This simulates the output of the wind farm if the

maximum limit of the DCWF is not raised immediately after implementing the third

WTG. The results from the simulation are shown in Table 20.

Figure 29: Simulation of Three WTGs - Limited Output

The results from the simulation are very similar to that of the simulation with the

DCWF consisting of two WTGs with limited output. This is expected, as the same

active and reactive power is generated and absorbed from the wind farm.

Table 20: Simulation Results of Three WTGs - Limited Output


1.44 MW -0.70 MVAr 0.967 pu 7.46%

78

6.6 Simulation of Three WTGs – Maximum Output

A simulation of the Denmark distribution system has been carried out with the

expanded DCWF operating at maximum potential output, 2.4 MW. This is shown

below in Figure 30, with a summary of the results shown in Table 21.

Figure 30: Simulation of Three WTGs - Maximum Output

The voltage at the POC with the expanded DCWF operating at maximum generation

has been found to be 0.996 pu, 10.69% more than when the wind farm has no

output. This simulation shows that three WTGs at the DCWF would substantially

push voltages outside of limits.

Table 21: Simulation Results of Three WTGs - Maximum Output


2.4 MW -1.16 MVAr 0.996 pu 10.69%

79

6.7 Simulation of Three WTGs with Q+ and STATCOM Option – No Output

The implementation of the third WTG with the ENERCON Q+ and STATCOM

option has been simulated in the simplified PowerFactory model. The third WTG is

modelled as a WTG at unity power factor. The Q+ and STATCOM technology is

modelled by the separate STATCOM connected to the T3 Bus Bar. Please note that

this is only for modelling purposes.

Figure 31: Simulation of Three WTGs with Q+ and STATCOM - No Output

Results from the simulation are shown in Table 22. The results show that with no

output from the WTGs, the voltage at the POC is now 0.932. This is higher due to

the injection of reactive power from the third WTG.

Table 22: Simulation Results of Three WTGs with Q+ and STATCOM - No Output


0 MW 0.6 MVAr 0.932 pu 3.67%

80

6.8 Simulation of Three WTGs with STATCOM Option – Limited Output

Simulation of the power-limited DCWF inclusive of the two existing WTGs and third

WTG with Q+ and STATCOM option has been performed, with the results shown in

Table 23.

Figure 32: Simulation of Three WTGs with Q+ and STATCOM - Limited Output

The results show that swing in voltage is substantially less due to the initial injection

of reactive power with no WTG output. Compared to the borderline operation of the

wind farm without the Q+ and STATCOM technology resulting in a 7.23% rise in

voltage, there is now only a 1.07% rise in voltage at the POC.

Table 23: Simulation Results of Three WTGs with Q+ and STATCOM - Limited Output


1.44 MW -1.07 MVAr 0.942 pu 1.07%

81

6.9 Simulation of Three WTGs with STATCOM Option – Maximum Output

Simulation of the DCWF with three WTGs operating at full output is shown in

Figure 33. The third WTG has been fitted wqith the Q+ and STATCOM option.

Results from the simulation are shown in Table 24.

Figure 33: Simulation of Three WTGs with Q+ and STATCOM - Maximum Output

The results from the simulation with the DCWF at full output of 2.4 MW show that

the DCWF is still within voltage limits. This confirms that the implementation of the

third WTG with Q+ and STATCOM would allow the wind farm to operate at its full

potential. The rise in voltage has been calculated from the difference in no

generation with STATCOM and Q+ and maximum generation.

Table 24: Simulation Results of Three WTGs with Q+ and STATCOM - Maximum Output


2.4 MW -1.37 MVAr 0.981 pu 5.26%

83

7. PROJECT COMPLICATIONS

A large part of the preceding analyses has been heavily dependent on the data

acquired from the ESS. The ESS logged environmental and generation data for both

WTGs at the DCWF to an acceptable degree, but was not perfect in logging data for

every 10-minute interval. Quality controlling confirmed 1364 10-minute intervals

were missing from the downloaded data, accounting for 2.6% of the total data.

The missing data was determined to be as a result of power outages to the DCWF for

various reasons, such as wind farm or transmission network maintenance, and

switching events due to storms or blackouts. This can be confirmed with

examination of the DCWF Outage Report provided by SkyFarming. The outages for

the analysis period were taken to be representative of an average year for the DCWF,

and so all data (not) logged during these periods has been omitted from the analysis.

It is also important to recognize the limitations of data-handling equipment of the

ESS. Firstly, the resolution of some of the logged data has been problematic. As the

energy produced by T1 and T2 in any 10-minute period has only been logged to one

significant figure, results from the “ENERCON SCADA system” generation analysis

may be erroneous. However, the small difference in results from the two WTGs

restricted analysis does not suggest the data is too misleading.

84

A further problem highlighting the limitations of data-logging instruments in the

ESS is the anemometer on the E-48 WTG. The anemometer is situated on the nacelle

of the WTG, and so may be subject to shading from the blades of the WTG. The

anemometers logging wind speeds for the ESS have no recorded accuracy

specifications, and so it has been difficult to assess the instrument’s reliability for the

generation analyses of the project. However, it must be noted that some

anemometers apply a correction factor prior to logging them wind speeds [18]; this

has been assumed for the purpose of the project.

One other possible solution is to apply a scaling factor to the wind speed

measurements so that they are scaled up proportionally to equal the energy

production logged by the ESS. This has not been implemented in the project due to

the resolution of the ESS logged energy measurement.

85

8. CONCLUSION

The DCWF in its current state consisting of two WTGs does not currently lose much

annual generation due to the currently imposed maximum power limit. Only 2.2% of

annual generation is lost. The raising of the maximum power of the wind farm in

this scenario may not be viable if it requires a costly investment.

However, with the addition of a third WTG to the wind farm, the annual generation

lost due to the maximum power limit would increase to 18.7%. A third WTG

installed at the site with the currently imposed limit, even temporarily, would result

in an additional 29% in annual yield compared to two. It has been found that this

would produce a positive NPV of $2.8m with the system taking 8.7 years to pay back.

However, this would result in only 60% of the wind farms capacity being utilised.

The DCWF would produce 7639 MWh annually if a third WTG with no restrictions

were installed. The WTG would only take 4.8 years to pay itself off, with a NPV of

$7.1m. This is substantially more than if the WTG were installed when the wind farm

was restricted. Thus, it becomes apparent the need to increase the maximum power

limit.

The expansion of the DCWF with the installation of a 1 MW/ 4 MWh BESS would

result in the wind farm maintaining the maximum output for much longer.

Operating in MGM, the DCWF would gain an additional 309 MWh annually with

86

the selected VRB technology, or an additional 413 MWh annually with the selected

LIB technology. However, both BESS options took longer than the project lifetime to

pay back. Thus, the conclusion has been made that the implementation of utility-

scale battery storage at the DCWF is currently not economically feasible. However,

an economic model of the BESS options has been undertaken for three years’ time.

The systems have been shown to be much more economically feasible if installed in

near future.

Operation of the BESS in PSM may attract additional capacity credits and arbitrage if

a new PPA were agreed to. Although the economic feasibility of the battery

operating in this way has not been investigated in this report, the concept warrants

further investigation. This may be able to be researched in more detail in future if

additional financial information were acquired from the DCWF Board.

A solution has been presented that would allow the expanded DCWF to overcome

the problem of voltage rise and generate at its maximum potential. The

implementation of a third WTG with the Q+ and STATCOM feature would allow for

a much smaller swing in voltage from no wind farm output to full wind farm output.

The impact of this system on the Denmark distribution network has been simulated

in PowerFactory, with the outcome proving that the solution would satisfy the

voltage limits. However, the model has been greatly simplified due to the limited

amount of information available. In future, a more detailed PowerFactory model

could be developed that would provide a much more accurate study.

87

9. REFERENCES

[1] Denmark Community Windfarm, "Location," Denmark Community Windfarm Ltd, 2013. [Online]. Available: http://www.dcw.org.au/location.html. [Accessed December 2016].

[2] Denmark Community Windfarm Ltd, "History," 2013. [Online]. Available: http://www.dcw.org.au/history.html. [Accessed November 2016].

[3] Denmark Community Windfarm Ltd, "The Project," 2013. [Online]. Available: http://www.dcw.org.au/project.html. [Accessed November 2016].

[4] ENERCON, "ENERCON Product Overview," Germany, Aurich, 2015.

[5] Western Power, "What we do," Western Power, 2016. [Online]. Available: https://www.westernpower.com.au/about/what-we-do/. [Accessed Novemeber 2016].

[6] A. Woodroffe, Interviewee, A Tale of Two Windfarms (SkyFarming). [Interview]. 2016.

[7] C. L. Masters, "Voltage Rise The Big Issue When Connecting Embedded Generat On To Long 11 Kv Overhead Lines," Power Engineering Journal, vol. February, pp. 5-12, 2002.

[8] Western Power, "Technical Rules," Western Power, Perth, 2011.

[9] M. Calais, "Power Quality and Wind Power," Murdoch University, Perth, 2016.

[10] G. Boyle, Renewable Energy: Power for a Sustainable Future, Oxford: Oxford University Press, 2012.

[11] Clean Energy Council, "Energy Storage," Clean Energy Council, [Online]. Available: https://www.cleanenergycouncil.org.au/technologies/energy-storage.html. [Accessed 12 August 2016].

[12] AECOM, "Energy Storage Study," Australian Renewable Energy Agency, Sydney, 2015.

[13] Lazard, "Lazard's Levelised Cost of Storage Analysis," 2015.

[14] D. Elliott, Balancing Green Power, Bristol: IOP Publishing, 2016.

[15] M. Brower, Wind Resource Assessment: A Practical Guide to Developing a Wind Project, New Jersey: John Wiley & Sons, 2012.

[16] AWS Scientific, Inc., Wind Resource Assessment Handbook, New York: National Renewable Energy Laboratory, 1997.

[17] Australian Energy Market Operator, "Facility Scada," Australian Energy Market Operator, 2015/2016. [Online]. Available: http://data.wa.aemo.com.au/#facility-scada. [Accessed October 2016].

[18] C. Mademlis, "Influence of the Measurement Accuracy of Wind Sensors on Wind System Performance," Aristotle University of Thessaloniki, Greece.

[19] S. Stankovic, N. Campbell and A. Harries, Urban Wind Energy, London: Earthscan, 2009.

[20] UK Government, "Digest of UK Energy Statistics," 30 July 2015. [Online]. Available:

88

https://www.gov.uk/government/collections/digest-of-uk-energy-statistics-dukes. [Accessed 20 September 2016].

[21] T. Wizelius, Developing Wind Power Projects, London: Earthscan, 2007.

[22] D. A. J. R. R. M. Dell, Understanding Batteries, The Royal Society of Chemistry: Cambridge, 2001.

[23] X. Xie, "Vanadium Redox-Flow Battery," 25 November 2011. [Online]. Available: http://large.stanford.edu/courses/2011/ph240/xie2/. [Accessed December 2016].

[24] Hydro Tasmania, "King Island Renewable Energy Integration project," Hydro Tasmania, 2014. [Online]. Available: http://www.kingislandrenewableenergy.com.au/project-information/energy-storage-system. [Accessed january 2017].

[25] Australian Vanadium Limited, "Vanadium Batteries," Australian Vanadium Limited, 2017. [Online]. Available: http://australianvanadium.com.au/vanadium-batteries/. [Accessed January 2017].

[26] Gildemeister, "CellCube FB 250-1000," [Online]. Available: http://www.vsun.com.au/wp-content/uploads/CellCube-250-1000.pdf. [Accessed December 2016].

[27] e. a. Xing Luo, "Overview Of Current Development In Electrical Energy Storage Technologies And The Application Potential In Power System Operation," Applied Energy, vol. 137, pp. 511-536, 2015.

[28] Gildemeister, "Product Line Presentation CellCube," Gildemesiter, 2016.

[29] S. Santhanagopolan, Design and Analysis of Large Lithium-Ion Battery Systems, London: Artech House, 2015.

[30] Are We Any Closer, "Lithium Ion Battery Primer," Are We Any Closer, May 2013. [Online]. Available: https://areweanycloser.wordpress.com/2013/05/20/lithium-ion-battery-primer/. [Accessed December 2016].

[31] T. R. David Linden, Handbook of Batteries, New York: Mcgraw-Hill, 2002.

[32] Australian Government, "Bureau of Meteorology," Commonwealth of Australia, 2017. [Online]. Available: http://www.bom.gov.au/. [Accessed 6 January 2017].

[33] Climate Council, "Powerful Potential: Battery Storage for Renewable Energy and Electric Cars," Climate Council, Australia, 2015.

[34] S. Tachikawa and T. Yachi, "Economical Evaluation of Photovoltaic and Battery Systems under Real-time Pricing (RTP)," Tokyo University of Science, Tokyo, 2013.

[35] International Renewable Energy Agency, "Battery Storage For Renewables: Market Status And Technology Outlook," IRENA, Abu Dhabi, 2015.

[36] Australian Energy Market Operator, "Short-Term Energy Market (STEM) Summary," AEMO, 2016. [Online]. Available: https://www.aemo.com.au/Electricity/Wholesale-Electricity-Market-WEM/Data/Price-limits. [Accessed January 2017].

[37] Jacobs, "Retail Electricity Price History And Projections - Public," AEMO, Australia, 2016.

89

[38] Mercari, "LGC Closing Rates," Mercari, 17 January 2017. [Online]. Available: http://lgc.mercari.com.au/. [Accessed 7 January 2017].

[39] Green Energy Markets, "LGC Market Prices," Green Energy Markets, 2016. [Online]. Available: http://greenmarkets.com.au/resources/lgc-market-prices. [Accessed January 2017].

[40] Australian Energy Market Operator, "Assignment of Capacity Credits," 2016. [Online]. Available: https://www.aemo.com.au/Electricity/Wholesale-Electricity-Market-WEM/Reserve-capacity-mechanism/Assignment-of-capacity-credits. [Accessed January 2017].

[41] ENERCON, "Technical Data - ENERCON Grid Technology," ENERCON, 2016. [Online]. Available: http://www.enercon.de/en/technology/grid-technology/. [Accessed January 2017].

[42] Western Power, "Denmark Community Wind Farm Study Summary," Western Power, Perth, 2012.

[43] L. Z. William Shepherd, Electricity Generation Using Wind Power, England: World Scientific Pub Co Inc, 2011.

[44] Western Power, "Denmark Community Wind Farm Study Summary," Western Power, Perth, 2012.

[45] Western Power, "Guidelines for connection of generators," Western Power, Perth, 2016.

[46] C. A.-C. a. S. R.-M. Francisco Bañuelos-Ruedas, "Methodologies Used in the Extrapolation of Wind Speed Data at Different Heights and Its Impact in the Wind Energy Resource Assessment in a Region," 2011. [Online]. Available: http://www.intechopen.com/books/wind-farm-technical-regulations-potential-estimation-and-siting-assessment/methodologies-used-in-the-extrapolation-of-wind-speed-data-at-different-heights-and-its-impact-in-th. [Accessed 19 September 2016].

[47] Denmark Community Windfarm Ltd, "The Turbines," Denmark Community Windfarm Ltd, 2013. [Online]. Available: http://www.dcw.org.au/turbine.html. [Accessed November 2016].

[48] U.S. Department of Energy, "Vanadium Redox Flow Batteries," October 2012. [Online]. Available: https://energy.gov/sites/prod/files/VRB.pdf. [Accessed January 2017].

[49] Nexeon, "About Li-ion Batteries," Nexeon, 2017. [Online]. Available: https://www.nexeon.co.uk/about-li-ion-batteries/. [Accessed January 2017].

[50] Synergy, "Synergy Smart Home Plan," Synergy, 2017. [Online]. Available: https://www.synergy.net.au/Your-home/Energy-plans/Smart-Home-Plan. [Accessed January 2017].

91

10. LITERATURE REVIEW

10.1 Developing Wind Power Projects

This textbook, published in 2007, provides an insight into the overall development,

from planning to commissioning, of large-scale wind farms. It has been useful in

helping to develop a broad understanding of the concepts involved in the operation

of a wind farm; the text provides general information on all key steps involved,

instead of very detailed information on a particular step. Specifically, the text has

been referred for recollection of concepts previously learnt throughout university

studies, including wind characteristics (such as turbulence and roughness classes),

wind energy yield (such as speed and height relationships), and wind turbine types

and components (such as methods of power control and generator type). [21]

10.2 Urban Wind Energy

“Urban Wind Energy” is a textbook published in 2009 that has been very

knowledgeable in the feasibility analysis aspect of the thesis project. The book

provides various topics to consider when conducting a wind resource feasibility

analysis, including capacity factor of the site and potential energy yield in the wind.

Concepts have been used in the text to relate to the studies undertaken for the

DCWF thesis project; however, the book has been more useful in providing a means

to consider different ways of how the DCWF site could be analysed. [19]

92

10.3 Electricity Generation Using Wind Power

William Shepherd, Li Zhang

A much more technical literature, the text provides a detailed understanding into

the electrical power aspects of wind turbine generators. Of particular relevance to

the DCWF thesis project are the chapters “Power Flow in Electrical Transmission

and Distribution Systems” and “Integrating Wind Power Generation into an

Electrical Power System”. The textbook studies the impacts of wind farms on an

electrical network; this is very relatable to the problems that the SWIS experiences

in rural regions due to embedded generation. The text has also been referred to

during research into overcoming power limitations for the project. [42]

10.4 ENERCON E-48 Datasheet

ENERCON

The ENERCON E-48 datasheet, attached in Appendix A, has provided information

on the power produced at different wind speeds necessary to construct a power

curve for the WTGs at the DCWF. The formulated power curve has been used

extensively in the generation analyses conducted throughout the thesis project. [4]

93

10.5 Wind Resource Assessment: A Practical Guide to Developing a Wind Project

Michael Brower, Daniel Bernadett, Kurt Elsholz

This recent (2012) online textbook provides detailed data monitoring, logging, and

handling techniques for wind projects. The chapter “Data Analysis and Resource

Assessment” gives a step by step process of how to correctly quality control and

validate logged data, which has been extremely useful in the preliminary stages of

the generation analyses of the DCWF. Due to the huge amounts of data acquired

from the ESS and its’ importance to proceeding parts of the project, it has been

important to understand how to handle it correctly. The treatment of suspect and

missing data is also an important concept covered by the text. [15]

10.6 Denmark Community Wind Farm Study Summary

Western Power

This document from Western Power is a study summary conducted in 2012 (Revision

2) for the connection of the DCWF in its current state of operation. The document is

extremely useful in that it provides various studies of the wind farm from the utility’s

point of view; it provides the rules and regulations that Western Power must impose

upon the wind farm to ensure network stability. Load models, feeder currents, and

94

voltage profile studies are all presented in the document, which has assisted with the

analysis of the expanded wind farm for this thesis project. [41]

10.7 Voltage Impact Studies Investigating Reactive Power Control Modes of Inverter-Coupled Wind Generation Connected to a Weak Rural Feeder

Simon Taylor

This dissertation written by a previous student of Murdoch University examines the

impact of wind turbine generators on electricity networks that have weak rural

feeders, using Kalbarri Wind Farm and Denmark Community Windfarm as case

studies. Some parts of the DCWF thesis project have investigated overcoming power

limitations and voltage profile studies of the network, and so the research conducted

as part of Simon Taylor’s thesis project has been extremely valuable.

10.8 Design and Analysis of Large Lithium-Ion Battery Systems

Shriram Santhanagopalan

This textbook has helped immensely with the BESS design part of the project. Not

limited to LIBs, the text also contained information on the chemistry of the VRB

technology. Specifically, the book has helped with battery size and type selection.

[29]

95

11. APPENDICES

11.1 Appendix A: ENERCON E-48 WTG Specifications

Table 25: ENERCON E-48 WTG Power Produced Over Different Wind Speeds

Wind Speed (m/s)

Power (kW)

Power Coefficient

1 0.0 0.00

2 0.0 0.00

3 5.0 0.17

4 25.0 0.35

5 60.0 0.43

6 110.0 0.46

7 180.0 0.47

8 275.0 0.48

9 400.0 0.50

10 555.0 0.50

11 671.0 0.45

12 750.0 0.39

13 790.0 0.32

14 810.0 0.27

15 810.0 0.22

16 810.0 0.18

17 810.0 0.15

18 810.0 0.13

19 810.0 0.11

20 810.0 0.09

21 810.0 0.08

22 810.0 0.07

23 810.0 0.06

24 810.0 0.05

25 810.0 0.05

Developed Power Curve Equation

0.0107230392𝑥6 − 0.5116280162𝑥5 + 9.4788367194𝑥4 − 87.2620084372𝑥3 + 430.4929572715𝑥2 − 1,060.6424460003𝑥 + 1,017.3199263051

96

11.2 Appendix B: Powerfactory Model Parameters

Table 26: PowerFactory Network Parameters

Component Name Parameters

Grid Albany Substation V Setpoint = 1.02 pu

Bus Albany Nominal V = 22 kV

Distribution Line

Lower Denmark Feeder (LDF)

Z = 26.78 + 35.28j

Bus Denmark Point of Connection (POC)

Nominal V = 22 kV

Load Denmark Load P = 2 MW, Q = 0.969 MVAr

Shunt Capacitor Capacitor Bank Q = -1.4 Var

Distribution Line

WTGs to POC Z = 0.022 + 0.029j

Bus DCWF Nominal V = 22 kV

Transformer T1 Transformer 22 kV (D)/400 V (YN), Rated S = 1 MVA, Z = 6.25%, Losses = 7.75 kW



Bus T1 Nominal V = 400 V



Static Generator Turbine 1 P = Variable, Q = Variable, PF = 0.9 absorbing

Static Generator Turbine 2 P = Variable, Q = Variable, PF = 0.9 absorbing

Static Generator T3 Active P = Variable, Q = 0, PF = 1

Static Generator T3 Reactive P = 0 , Q = Variable, PF = 0

expansion study and performance analysis...

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