mine site village carbon emissions engineering offset ...i mine site village carbon emissions &...

i

Mine Site Village Carbon Emissions

&

Engineering Offset Solutions

Maxime Ploumis

A report submitted to the School of Engineering and Energy, Murdoch University

in partial fulfilment of the requirements for the degree of Bachelor of Engineering

Date issued: 25/11/2011

Business Supervisor: Paul Hardisty, Global Director of EcoNomics WorleyParsons

Academic Supervisors: - Dr Martin Anda, Chair of Environmental Engineering

- David Goodfield, PhD Candidate

i

Acknowledgments

Without the financial support provided by WorleyParsons as well as the invaluable support of

Paul Hardisty and his wealth of knowledge and industry experience, the Internship and report

would not have been possible. I am sincerely thankful for the opportunity and experience.

I owe my deepest gratitude to my academic supervisors, Martin Anda and David Goodfield,

for their encouragement, guidance and support during the entire progression of this project.

I would like to especially acknowledge Antony Piccinini for his guidance, in-depth

experience, highly valued recommendations and time in assisting me with this project.

I am also thankful to all the following people whom have made time available to assist in a

number of ways, to make the completion of this project possible:

Professor Trevor Pryor whose enormous knowledge about renewable energy power systems

as well as HOMER has greatly contributed to this project.

Colin Hayes and Steve Lucks for having assisted me with the geothermal section of this

study.

Bruce Clare and Wayne Brindley with their expertise on mine sites‟ power systems.

Brett Rice, James Rhee and Chem Nayar for providing me great recommendations and

accurate quotes from the different product they sell.

Paul Wilkinson and Bruce Kingston for their help with the commissioning of Mount Magnet

Gold village‟s monitoring system.

ii

Executive Summary

This report aims to investigate solutions for carbon neutrality in mine site village

developments by assisting David Goodfield (DG) in undertaking several essential tasks

associated with his PhD, using Mount Magnet Gold (MMG) village as a case study.

In order to assess the potential of Renewable Energy (RE) as a carbon offset solution in the

current power system, software called REMAX was specially developed. HOMER was used

to assess the potential of RE in standalone power systems. A standalone study was

undertaken, as major capital cost savings were identified if the transmission line between the

mine power system and the village was removed (≈$250,000 per kilometre). The sensitivity

of MMG village‟s power system, being the mine‟s power system was found to be somewhere

between 50 and 100 kW. Due to these sensitivities and the small ratio of the village within

the load (2.46%), it was found that the potential of RE in the current power system would be

very low. The standalone configuration was found to be more economically viable than the

current power system, if the village is located more than 4 kilometres (km) away from the

mine power system (assuming cost of the line ≈$250,000 per kilometre). Findings also show

that a wind diesel hybrid power system is more economically viable than the diesel, only if

the project life is more than 7, 5, 4 and 3 years for a project starting in January 2012, 2014,

2016 and 2018 respectively. However, in the situation where the standalone system is

powered by only diesel generators, the carbon emission was found to be higher and was not

suitable for this project.

Given the high energy usage of mining villages‟ air conditioning (AC) systems, the potential

of using a Ground Source Heat Pump (GSHP) system instead of currently used standard

reverse cycle AC systems was also investigated. GSHPs were found to have a high potential

as a carbon offset solution in mine site villages, with payback period under six years possible.

Nevertheless, the system needs to be sized appropriately and used in high demand locations

(≈20 hours a day).

Another task associated with this project was to undertake the village‟s energy audit and

monitoring system commissioning which were successfully undertaken during a site visit in

the third week of October 2011. Also, the calculation of the embodied energy of two

buildings (donga and kitchen) from the village was undertaken using a life cycle assessment

software (eTool), that was previously investigated.

iii

Nomenclature

AC: Air conditioning

BOM: Bureau of meteorology

DG: David Goodfield

CAPEX: Capital expenditure

CO2: Carbon dioxide

COP: Coefficient of performance

E: Enercon

FWS: Four Wind Seasons

GSHP: Ground source heat pump

LGCs: Large-scale generation certificates (RECs)

OPEX: Operational expenditure

MM: Mount Magnet

MMG: Mount Magnet gold

NPC: Net Present Cost

NPV: Net Present Value

PL: Project life

PV: Photovoltaic

RE: Renewable energy

WT: Wind turbine

WTP: Water treatment plant

WWTP: Waste water treatment plant

iv

Table of Content

1 Introduction ........................................................................................................................... 1

2 Literature review ................................................................................................................... 2

2.1 Potential of renewable energy as a carbon offset solution in mine site villages ....... 2

2.2 Case studies ............................................................................................................... 3

2.3 Geothermal air conditioning ...................................................................................... 4

3 Mount Magnet gold village renewable energy power system .............................................. 6

3.1 Mount Magnet gold village background ................................................................... 6

3.2 Renewable energy power systems ............................................................................. 7

3.2.1 Predicted load ........................................................................................... 8

3.2.2 Current power system background ......................................................... 11

3.2.3 Identification of renewable energies and resource assessment ............... 14

3.2.4 Technology identification and selection ................................................. 33

3.2.5 RE power system analysis ...................................................................... 36

4 Geothermal air-conditioning potential in mining villages .................................................. 69

4.1 Current system background ..................................................................................... 69

4.2 Geothermal heat pump technology .......................................................................... 71

4.2.1 Ground water systems ............................................................................. 72

4.2.2 Ground heat exchanger systems ............................................................. 73

4.2.3 Surface water heat exchanger system ..................................................... 74

4.3 GSHP at MMG village ............................................................................................ 75

4.4 GSHP system sizing ................................................................................................ 77

4.4.1 Load calculation ...................................................................................... 77

4.4.2 System sizing and cost estimations ......................................................... 78

4.4.3 Potential of GSHP at MMG village analysis .......................................... 82

5 David Goodfield‟s PhD ....................................................................................................... 92

v

5.1 Preparation of Monitoring Devices for MMG village ............................................. 92

5.2 Investigation of different software for operational and embodied energy calculation

of MMG village .............................................................................................................. 92

5.3 Diagram modification.............................................................................................. 94

5.4 MMG village monitoring system commissioning ................................................... 95

5.4.1 MMG village site visit and monitoring system commissioning ............. 95

5.4.2 Commissioning results ............................................................................ 98

5.5 MMG village embodied and operational energy calculations ............................... 100

5.6 MMG village energy audit .................................................................................... 101

6 Recommendations ............................................................................................................. 102

6.1 Recommendations for the full completion of this study ....................................... 102

6.2 Recommendations for future interest .................................................................... 103

7 Conclusion ......................................................................................................................... 104

7.1 Potential of RE power systems as a carbon emission offset solution ................... 104

7.2 Potential of GSHP systems as a carbon emission offset solution ......................... 105

7.3 Recommendations ................................................................................................. 105

8 Reference ........................................................................................................................... 106

9 Appendix ........................................................................................................................... 110

9.1 Case Studies .......................................................................................................... 110

9.1.1 Mount Cattlin ........................................................................................ 110

9.1.2 Mount Isa Mines ................................................................................... 111

9.1.3 Nickel mines “X” and “Y” .................................................................... 111

9.2 Solar resource investigation .................................................................................. 113

9.3 Wind resource investigation .................................................................................. 113

9.3.1 BOM data .............................................................................................. 113

9.3.2 NASA Data ........................................................................................... 114

9.4 Current power system costing ............................................................................... 121

9.5 Multi-criteria analysis............................................................................................ 122

vi

9.5.1 MCA criteria weighting ........................................................................ 122

9.5.2 MCA outcome ....................................................................................... 123

9.6 Project‟s contacts ................................................................................................... 126

9.7 Costs ...................................................................................................................... 128

9.8 Software input information ................................................................................... 136

9.8.1 Wind turbine input information ............................................................ 136

9.8.2 PV input information ............................................................................ 137

9.8.3 Large-scale generation certificates (LGCs) assumption ....................... 138

9.8.4 Natural gas and diesel carbon content calculation ................................ 138

9.8.5 RE Potential in the current power system ............................................. 139

9.8.6 Standalone analysis ............................................................................... 170

9.9 Geothermal air conditioning information .............................................................. 174

9.10 Monitoring equipment information ....................................................................... 174

9.11 Software investigation results ............................................................................... 176

9.12 MMG village energy audit .................................................................................... 177

vii

List of Figures and Tables

Figures:

Figure 1: Mount Magnet Location ............................................................................................. 6

Figure 2: RE potential assessment methodology used ............................................................... 7

Figure 3: MMG village electricity use forecast from June 2011 to November 2013 (BEC

engineering, 2011) ..................................................................................................................... 8

Figure 4: Energy use repartition at MMG mine (BEC engineering, 2011) ............................... 9

Figure 5: MMG village Daily Electricity use assumption for February .................................. 10

Figure 6: MMG village Daily Electricity use assumption for September ............................... 10

Figure 7: Mount Magnet gold mine power system .................................................................. 11

Figure 8: Mount Magnet gold mine power system and loads .................................................. 12

Figure 9: Resource assessment methodology used .................................................................. 14

Figure 10: Annual daily average solar exposure in Australia (ERIN, 2008) ........................... 15

Figure 12: Predicted load and solar resource seasonal variation comparison over the year

(BOM, 2011 and BEC, 2011) .................................................................................................. 17

Figure 13: Australia‟s rainfall map (Kuwahata et al. 2010) .................................................... 19

Figure 14: MM topographic map (One line represents 20m elevation) (Google Maps, 2011)19

Figure 15: Mean wind speed at 80m above ground level in Australia (ERIN, 2008) ............. 20

Figure 16: Monthly average wind speed seasonal variation at 10m above ground surface at

Mount Magnet (BOM, 2011) ................................................................................................... 22

Figure 17: Long term daily diurnal variation in the monthly average hourly wind speed for

January, April, July and October at 10m above ground surface at Mount Magnet (BOM,

2011) ........................................................................................................................................ 23

Figure 18: Annual average wind rose at 10m above ground level at Mount Magnet in m/s

(BOM, 2011) ............................................................................................................................ 23

Figure 19: Frequency distribution wind speed at 10m above ground surface at Mount Magnet

(BOM, 2011) ............................................................................................................................ 24

Figure 20: Wind speed cumulative probability function at 10m above ground level at Mount

Magnet (BOM, 2011)............................................................................................................... 24

Figure 21: Weibull distribution factor estimation graph of wind speed 10m above ground

surface ...................................................................................................................................... 25

Figure 22: Load and wind resource seasonal variation comparison over the year (BOM, 2011)

.................................................................................................................................................. 26

Figure 23: Land use in Western Australia (Commonwealth of Australia, 2001) .................... 28

Figure 24: Non-urban railway lines covered by WA rail access regime (ERA, 2011) ........... 29

Figure 25: Western Australia crop production estimates for 2010-2011 (ABARE, 2011) ..... 29

Figure 26: Australia‟s wave resource map (Herman, 2011) .................................................... 30

Figure 27: Ground temperature at 5km below ground surface in Australia (Ecogeneration,

2011) ........................................................................................................................................ 31

Figure 28: 50th

percentile of hourly tidal current speed in meter per second (Griffin et al.

2010) ........................................................................................................................................ 32

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Figure 29: HOMER: Generator input screen shot 1 ................................................................ 40

Figure 30: Load and solar resource on different surface tilt angles seasonal variation

comparison at MM (NASA, 2011). ......................................................................................... 41

Figure 31: Annual average solar resource on different surface tilt angles at MM (NASA,

2011) ........................................................................................................................................ 41

Figure 32: Cost per installed Watt versus wind turbine capacity. ........................................... 43

Figure 33: NPC difference with current power system per ton of CO2 emissions offset

(Project life of 9 years) ............................................................................................................ 49

Figure 34: NPC difference with the current power system per tonne of CO2 emissions offset

(Project life of 8 years) ............................................................................................................ 50

Figure 35: NPC analysis of different systems‟ configuration for a project starting in January

2012 with different project life. ............................................................................................... 51

Figure 36: Projected installed PV cost ..................................................................................... 52

Figure 37: Projected installed wind turbine cost...................................................................... 53







Figure 41: NPC analysis comparison of the standalone and current power system located at 2,

4 and 6 kilometres away from the village for different project lives (Transmission line cost:

$250,000 per km) ..................................................................................................................... 58

Figure 42: CO2 emissions comparison for a project starting in January 2012 ......................... 59

Figure 43: HOMER output screen shot for project starting in January 2012 with sensitivity

analysis on PV cost and project life ......................................................................................... 60




Figure 47: Investigated wind turbines‟ power curves comparison .......................................... 65

Figure 48: Investigated wind turbines‟ power curves comparison (Zoomed in view) ............ 66

Figure 49: MMG village and possible RE power system location at Mount Magnet ............. 66

Figure 50: Ground source heat pump schematic diagram ....................................................... 71

Figure 51: Groundwater system schematic (McQuay, 2002) .................................................. 72

Figure 52: Horizontal ground loop system (McQuay, 2002) ................................................... 73

Figure 53: Vertical Ground loop system (McQuay, 2002) ...................................................... 74

Figure 54: Surface water system (McQuay, 2002) .................................................................. 75

Figure 55: Water to water heat pump configuration for Dongas ............................................. 76

Figure 56: Water to air heat pump configuration for Dongas .................................................. 76

Figure 57: Water to water heat pump configuration for large rooms ...................................... 76

Figure 58: Heat and cool flow of the heating and cooling mode of a GSHP system .............. 77

Figure 59: GSHP system capital cost sensitivity analysis (Capital cost: $1,001,256.96) ....... 84

Figure 60: Annual heating and cooling load sensitivity analysis ............................................ 84

Figure 61: Annual water heating load sensitivity analysis ...................................................... 85

ix

Figure 62: Capital cost sensitivity analysis for the 50kW system operating 20 hours a day

(Capital cost: $185,000) ........................................................................................................... 87


(Capital cost: $185,000) ........................................................................................................... 90

Figure 64: Capital cost sensitivity analysis comparison for the 50kW system operating 10 and

20 hours a day (Capital cost: $185,000) .................................................................................. 91

Figure 65: Original conceptual model for carbon neutral mine site village (Goodfield, 2011)

.................................................................................................................................................. 94

Figure 66: Updated conceptual model for carbon neutral mine site village (Goodfield, 2011)

.................................................................................................................................................. 95

Figure 67: MMG village‟s monitoring devices configuration ................................................. 97

Figure 68: Side view of monitoring bores set up near MMG village ...................................... 97

Figure 69: Monitoring bore location at MM ............................................................................ 98

Figure 70: Hobolink screen shot of online access of monitoring devices (HOBOlink, 2011) 98

Figure 71: Hobolink screen shot of Kitchen monitoring sensors readings (HOBOlink, 2011)

.................................................................................................................................................. 99

Figure 72: Sample of kitchen hot water system power use from live collected data (1) ......... 99

Figure 73: Sample of kitchen hot water system power use from live collected data (2) ....... 100

Figure 74: eTool screen shot of one Donga embodied energy calculation model (eTool, 2011)

................................................................................................................................................ 101

Figure 75: Energy use repartition at “X” mine per year ........................................................ 112

Figure 76: Energy use repartition at “Y” mine per year ........................................................ 112

Figure 11: Mount Magnet best, worst and average mean monthly global solar exposure over

1990 to 2010 (BOM, 2011) .................................................................................................... 113


Mount Magnet (NASA, 2011) ............................................................................................... 115

Figure 78: Long term daily diurnal variation in the monthly average hourly wind speed for

each month of the year at 50m above ground surface at Mount Magnet (NASA, 2011) ...... 116

Figure 79: Annual average wind rose at 50m above ground level at Mount Magnet (NASA,

2011) ...................................................................................................................................... 116


(NASA, 2011) ........................................................................................................................ 117


Magnet (NASA, 2011) ........................................................................................................... 117


surface .................................................................................................................................... 118

Figure 83: Load and wind resource seasonal variation comparison over the year (NASA,

2011) ...................................................................................................................................... 119

Figure 84: BOM purchased wind data annual average wind speed at MM (BOM, 2011) .... 120

Figure 85: LGCs‟ cost history from October 2010 to October 2011 ..................................... 138

Figure 86: NPC analysis of different PV array sizes with a project life of 5 years ............... 139



Figure 89: NPC analysis of different PV array sizes with a project life of 12 years ............. 140

x



Figure 92: NPC of different PV array size versus project life ............................................... 141











Figure 103: NPC analysis of different PV array sizes with a load factor of 1 ....................... 147






Figure 109: NPC analysis of different wind turbine configurations with a project life of 5

years ....................................................................................................................................... 150


years ....................................................................................................................................... 150


years ....................................................................................................................................... 151


years ....................................................................................................................................... 151


years ....................................................................................................................................... 152

Figure 114 : NPC analysis of wind turbine configurations with a project life of 5 years ..... 152

Figure 115: NPC analysis of wind turbine configurations with a project life of 7 years ...... 153



Figure 118: NPC analysis of wind turbine configurations with a project life of 12 years .... 154











xi





Figure 133: NPC analysis of different wind turbine configurations with a load factor of 1 . 162






Figure 139: NPC analysis of different wind turbine and PV array configuration with a project

life of 12 years ....................................................................................................................... 165


life of 15 years ....................................................................................................................... 165


life of 18 years ....................................................................................................................... 166


life of 5 years ......................................................................................................................... 166


life of 7 years ......................................................................................................................... 167


life of 8 years ......................................................................................................................... 167


life of 9 years ......................................................................................................................... 168

Figure 146: NPC analysis of different system configuration with a project life of 5 years .. 168




Figure 150: HOMER output screen shot for project starting in January 2012 ...................... 170




Figure 154: HOMER output screen shot for project starting in January 2012 and an average

daily load of 8568 kWh.......................................................................................................... 172


daily load of 8568 kWh (Graph representation) .................................................................... 172


daily load of 17136 kWh........................................................................................................ 173


daily load of 17136 kWh (Graph representation) .................................................................. 173

Figure 158: SimaPro “Wooden Shed” tutorial output summary (SimaPro, 2011) ................ 176

Figure 159: GaBi “Steel Paper Clip” tutorial plan (GaBi, 2011) .......................................... 176

xii

Tables:

Table 1: MMG village load characteristics (BEC engineering, 2011) ...................................... 9

Table 2: Generators Powering MMG Mine Operations and Village (Cummins Power, 2007)

.................................................................................................................................................. 12

Table 3: Mount Magnet gold mine power system leasing associated cost (BEC engineering,

2011) ........................................................................................................................................ 13

Table 4: Power supply information (Matricon, 2011M) .......................................................... 13

Table 5: Mount Magnet best, worst and average annual mean monthly global solar exposure

from 1990 to 2010 (BOM, 2011) ............................................................................................. 16

Table 6: Range test specification (AWS, 1997)....................................................................... 21

Table 7: Monthly and annual average wind speed at 10m above ground surface at Mount

Magnet (BOM, 2011)............................................................................................................... 22

Table 8: Selected Social, Environmental and Economic Criteria for MMG village RE power

system (Hardisty, 2010 and Wang et al. 2009) ........................................................................ 34

Table 9: MMG village RE power system project stakeholders ............................................... 34

Table 10: MCA final outcome ................................................................................................. 36

Table 11: Project information inputs ....................................................................................... 39

Table 12: REMAX: Project information inputs ....................................................................... 39

Table 13: REMAX: Generator information inputs .................................................................. 40

Table 14: PV information inputs.............................................................................................. 42

Table 15: Four Wind Seasons 50 and 100 kW wind turbines information inputs (WT: Wind

Turbine and FWS: Four Wind Seasons) .................................................................................. 42

Table 16: REMAX input and output information .................................................................... 44

Table 17: REMAX‟s outputs validation for current power system for 2012 .......................... 46

Table 18: REMAX‟s PV and wind turbine outputs validation with HOMER ........................ 46

Table 19: Projected installed cost of the investigated wind turbine ........................................ 53

Table 20: HOMER output summary for project starting in January 2012 (Generators: low

load cycle REGEN Power generators (150kW + 100kW + 50kW)) ....................................... 57







Table 24: MMG village AC unit number and size (Based on cooling capacity) ..................... 70

Table 25: Current AC system installed cost estimation (SPLIT 4 YOU, 2011) ...................... 70

Table 26: Cooling load calculation .......................................................................................... 78

Table 27: MMG village GSHP number and size (Cell coloured in yellow are water to water

heat pumps and uncoloured cell water to air heat pumps) ....................................................... 79

Table 28: Available size of GSHP in Australia ....................................................................... 80

Table 29: Horizontal and vertical ground loop sizing and costing guidelines (McQuay, 2002)

.................................................................................................................................................. 80

Table 30: MMG village GSHP cost estimation (Cummings, 2008) ........................................ 81

xiii

Table 31: Payback period estimation comparison with current system (NPV: Net Present

Value) ....................................................................................................................................... 83

Table 32: 50kW GSHP system payback period estimation comparison with a current 50kW

AC system operating 20 hours a day ....................................................................................... 86


AC system operating 10hours a day ........................................................................................ 89

Table 34: Investigated software and comments ....................................................................... 93

Table 35: Weibull distribution factor graph calculation ........................................................ 113


Magnet (NASA, 2011) ........................................................................................................... 114

Table 37: Weibull distribution factor graph calculation ........................................................ 118

Table 38: Current Power System Predicted Cost for 2012 .................................................... 121

Table 39: Criteria weighting .................................................................................................. 122

Table 40: Rating guideline ..................................................................................................... 123

Table 41: MCA final outcome (Afgan N and Carvalho M, 2002) ......................................... 124

Table 42: Project‟s contact..................................................................................................... 126

Table 43: Wind turbines costs (Better Generation, 2009 and emails from contacts) ............ 128

Table 44: PV modules costs including GST (Apollo Energy, 2011) ..................................... 131

Table 45: Inverter cost (Apollo Energy, 2011) ...................................................................... 132

Table 46: Wind turbines input information ........................................................................... 136

Table 47: Installed PV array cost per kW investigation ........................................................ 137

Table 48: Natural gas and diesel carbon content ................................................................... 138

Table 49: Monitoring equipment information (OneTemp, 2011) .......................................... 174

Table 50: Outdoor energy audit ............................................................................................. 177

Table 51: Laundry energy audit ............................................................................................. 177

Table 52: Donga energy audit ................................................................................................ 178

Table 53: Administration energy audit .................................................................................. 178

Table 54: Toilet energy audit ................................................................................................. 179

Table 55: Recreational room energy audit ............................................................................. 180

Table 56: Gymnasium energy audit ....................................................................................... 180

Table 57: Kitchen energy audit .............................................................................................. 181

Table 58: WTP energy audit .................................................................................................. 183

Table 59: WWTP energy audit .............................................................................................. 183

Table 60: Ice room energy audit ............................................................................................ 184

1

1 INTRODUCTION

The increasing prominence of environmental issues over the past decade has seen improved

consideration of carbon emission issues. Carbon emissions are produced when fossil fuels are

burned, leading to the release of Carbon Dioxide (CO2) into the atmosphere. In the natural

carbon cycle, CO2 is then absorbed by flora. However, today, fossil fuels are being burned so

quickly that the flora is not able to absorb all the released CO2 leading to an excess

concentration in the atmosphere. This is one of the main factors causing global warming

which leads to climate change (The Carbonaccount, 2010).

The application of the carbon tax within the next year has raised the mining industry‟s

interest as it requires companies to quantify their carbon emissions.

The main aim of this project is to assist David Goodfield (DG), a PhD candidate at Murdoch

University, with his work at the Mount Magnet Gold (MMG) village. This includes the

development of a load profile, a level 2 energy audit under AS 3598:2000, as well as

calculating the full lifecycle carbon emissions of this mining village. This will be done in

aggregation of the carbon emission of food, freights, solid wastes, embodied energy in

materials, construction processes, energy use and the water cycle. It also includes a start in

the creation of software providing generic output of various carbon offset solutions for

carbon neutral mining village development. Additionally, another task associated with this

project is to assess the potential of Renewable Energy (RE) power systems and analyse the

potential of Ground Source Heat Pump (GSHP_ as a substitution to normal reverse cycle air

conditioning (AC) as economically viable carbon emissions offset solutions for mining

villages, using MMG village as a case study.

Whilst DG‟s PhD will refer to the three major components efficiency, education and

technology integration for carbon emissions reduction, this report focuses primarily on the

third, technology integration.

2

2 LITERATURE REVIEW

There have been many studies and books forecasting energy requirements to increase and

discussing the issue of climate change and need of alternative energy resources. In Principles

of Sustainable Energy (Kreith et al. 2011) the need to switch from “a fossil fuel based

economy to one that uses renewable energy” is referred to. Alternative energy resources

(Kruget, 2006) and Handbook of Energy Efficiency and Renewable Energy (Kreith et al.

2007) note that due to the predicted increase of petroleum products, the world will be in quest

for a suitable replacement energy source. Sustainable Development and Innovation in the

Energy Sector (Steger et al. 2005) highlights the concerns of international conferences and

other venues of greenhouse gas emissions. The political risk of depending on petroleum is

also brought forward and solutions such as RE provided and discussed. These literatures

present the main reasons for this project which are climate change and the need to switch to

RE in order to reduce greenhouse gases emissions or more precisely CO2 which is a major

climate change contributor. These books discuss the potential of different renewable energies

to contribute to the energy sector in general, and reinforce the fact that these have enormous

potential as carbon emission offset solutions.

2.1 POTENTIAL OF RENEWABLE ENERGY AS A CARBON OFFSET

SOLUTION IN MINE SITE VILLAGES

Several articles and reports discussing the requirements to transit toward more sustainable

ways of overlooking a project were found. In the mining sector, Young (2004) reviews the

establishment of a framework for sustainable development in the mining industry. He noted a

three stage approach to sustainable development. These are the following:

- “Stage one: pollution prevention, the movement from pollution control to prevention”

- “Stage two: product stewardship, minimizing all environmental impacts over the life

of a product”

- “Stage three: clean technology, updating production techniques to move into clean

technology”

This project is mainly focused on the third stage discussed in this article. This shows the

willingness of the industry to look into clean technologies.

2 Literature Review

3

A study that needs to remain anonymous for the purpose of this project was also found and

focused on the investigation of the design and construction of a mining village using “bureau

as usual, enhanced and leading practice approaches”. This report focuses on looking at

options to produce an “Eco-village”. It was noted that the authors investigated RE as an

option and provided several solutions. This shows that the mining industry is looking into

how to make their mining villages more sustainable and less energy consuming. When the

energy side was investigated, solar and wind energy were looked at. In this report, the PV

array investigated is based on general figures. But, the usage here is only investigated

theoretically. The PV array capability of producing energy is investigated depending on the

roof surface area of the camp. Peak load demands as well as RE penetration into the grid is

not considered. In addition, no economic analysis comparison with the current power system

is provided. Hence, no payback period or information about the system economic viability is

discussed. Only rough approximations about the PV array yearly yield are provided and no

modelling of the PV array at the specific location undertaken. For the wind investigation,

only two types of Wind Turbines are taken into consideration. In addition, when selecting the

most appropriate one, only general cost of energy is being considered for operational cost and

capital costs. No modelling of the wind turbine output on site depending on the load and wind

resource was undertaken. This makes this type of selection of wind turbine (WT) very poor

and irrelevant. Hence, in this study, the selection of the appropriate wind turbine was

undertaken using modelling software and hourly local weather data. In addition, it was

compared to the current power system and its economic viability assessed.

Patel (2006) discussed in his book Wind and Solar Power Systems, how the cost of solar and

wind energy has decreased due to “new developments in these technologies”. As Hearps and

McConnell (2001) note in their report entitled Renewable Energy technology Cost Review,

the cost of wind and solar energy is predicted to decrease during the next 20 years. This

shows the relevancy of this project to assess the economic viability of RE technologies in

today‟s and future‟s situations.

2.2 CASE STUDIES

Several case studies undertaking similar projects as this one were investigated. The Galaxy

lithium mine at Mount Cattlin, Xstrata Parkside mine at Mount Isa and two nickel mines (“X”

and “Y”) in the Pilbara region that cannot be named in this project due to confidentiality

reasons were investigated. These mines in particular were looked at due to the sustainable

2 Literature Review

4

approach they undertook (Mount Isa and Cattlin) or projected to undertake (Mount Cattlin, X

and Y). Background on these different mining projects is available in the appendices.

The information about these sites was gathered via email correspondence, organised meetings

and online researches (Xstrata, 2011). The main motivation behind these projects was to:

- Demonstrate the effectiveness of solar technology to communities in North West

Queensland (Mount Isa mine)

- Demonstrate that an environmentally sensitive approach to mining activities is

achievable (Mount Cattlin)

- Protect themselves against financial repercussions of the uncertainty of diesel pricing

and the soon to be introduced carbon tax (Mount Cattlin, X and Y)

- Advertise their green approach for long term economic and environmental benefits

(Mount Cattlin)

- Comply with governmental greenhouse gas reduction program (Mount Cattlin, X and

Y)

The motivation for these projects is very similar to the overall project. However, the Mount

Cattlin and Isa projects were not economically viable as only the technology and

environmental and economic benefits were demonstrated there. If the economic viability of

the technology is not demonstrated not many organisations will take sustainable development

measures into considerations . Hence, in this project, the economic viability of the technology

will be assessed.

2.3 GEOTHERMAL AIR CONDITIONING

As mentioned by Elmoudi et al. (2011) in their paper, AC is one of the highest energy using

components in residences and buildings. They also noted that reducing the energy use in this

area will lead to lower peak time demand and carbon emissions.

Matricon and Bruindam are two mine site village builders that investigate sustainable

development behaviour and strategies. Matricon include investigation into ways of reducing

AC electricity usage at several mining villages located in Australia. Their report needs to

remain anonymous for the purpose of this study, written “to provide a major mining

organisation with the opportunity to reduce greenhouse gas contribution through

appropriate mitigation actions that result in energy cost savings to fund these

improvements”. This shows that the industry is looking at reducing their energy use using

2 Literature Review

5

economically viable solutions. This reinforces the need for this project, including assessment

of the potential of GSHPs as an alternative solution to standard reverse cycle AC units

currently being used. SKM was also contracted to undertake an environmentally sustainable

design for a classic mining camp (SKM, 2011). This took into considerations of the AC

system.

Elmoudi et al. (2011), Matricon, Bruindam and SKM have investigated AC systems in their

study but only focused on maximising the efficiency of the currently used reverse cycle AC

system. They did not investigate other systems such as solar and geothermal AC. Geothermal

AC systems were called by the USA‟s Environmental Protection Agency as the most

efficient, readily available way for residential AC (BUILD, 2011). Hence, in this project,

GSHP systems will be investigated and their potential assessed and compared with currently

used standard reverse cycle AC systems.

6

3 MOUNT MAGNET GOLD VILLAGE RENEWABLE ENERGY

POWER SYSTEM

3.1 MOUNT MAGNET GOLD VILLAGE BACKGROUND

MMG village is located about 570 km North East of Perth and 340 km East North East of

Geraldton (Google Maps, 2011). Ramelius Resources purchased the MMG mine from

Harmony gold mining company limited and contracted Matricon to build a new village on the

previously demolished site. This led to the creation of MMG village. This village is designed

to accommodate 160 workers and estimated to have an occupancy rate of around 80%. The

mining village is located on the North-East end side of Mount Magnet (MM) town and about

4 kilometres from the mine‟s operations. The village includes 40 dongas, 2 laundries, one

gymnasium, a recreational room, a Waste Water Treatment Plant (WWTP), a Water

Treatment Plant (WTP) and one kitchen. The village is built to have a life expectancy of 20

years and extra dongas are expected to be added fairly soon.

(http://www.welt-atlas.de/datenbank/karten/karte-3-905.gif)

Figure 1: Mount Magnet Location

http://www.welt-atlas.de/datenbank/karten/karte-3-905.gif

3 MMG Village RE Power System

7

3.2 RENEWABLE ENERGY POWER SYSTEMS

Renewable energy power systems have now been around for hundreds of years. These

systems are structures used to harness RE and convert it to useable energy to power a group

or single facility (Kaltschmitt et al. 2007).

RE can be defined as energy from natural resources which are naturally restored. The

different types of REs are discussed below.

The methodology used in this section can be observed in Figure 2. Before assessing the

potential of RE power systems in MMG village, the energy demand and current power

system in use must be understood. First, a background on the current power system at MMG

village is undertaken and forecasted energy demand is analysed. Then the different RE

resources available on site are identified and studied. Once achieved the diverse technologies

available to convert the available REs into electricity were identified and the most

appropriate ones selected. Finally, the most appropriate RE systems for different project lives

were selected and their potential as an economically viable carbon emission offset solution

analysed.

Figure 2: RE potential assessment methodology used


8

3.2.1 PREDICTED LOAD

The predicted load was used, as not enough real life data has been collected to date to

produce a yearly load profile. The energy demand of the village was predicted by BEC

engineering.

The predicted power demand estimated in BEC engineering report was used to create a load

profile of the MMG village and can be observed in Figure 3 below. The monthly maximum

power consumption was predicted to be in January and February as seen in Table 1 due to

peak AC requirements. A pie chart was also produced to observe the impact of the village‟s

energy demand compared with the mine operation. As it can be seen in Figure 4, the village

has predicted annual electricity demand of 2.46% of the entire mine.

Figure 3: MMG village electricity use forecast from June 2011 to November 2013 (BEC

engineering, 2011)

60

80

100

120

140

MWh/mth

Month

MMG village electricity use forecast


9

Table 1: MMG village load characteristics (BEC engineering, 2011)

Predicted Comments

Maximum

Demand 300 kW

Predicted assuming maximum demand of

1.5kW per room. This takes into account

the kitchen, water treatment plant and

vacant rooms. It is based on a 200 rooms

village.

Average power

demand 124 kW Averaged throughout one year

Maximum

monthly energy

use

130 MWh In January and February

Minimum

monthly energy

use

65 MWh In September

Annual energy

use 1.09 GWh

Calculated using the following formula:

300kW x 30% x 1.37annual average factor

x 24hrs/day x 365days/yr

Figure 4: Energy use repartition at MMG mine (BEC engineering, 2011)

33.95%

24.52%

31.20%

1.55% 1.31%

2.46% 2.05% 1.22% 1.74%

Energy use repartition at MMG Mine

SAG Mill

Secondary Mill

Mill Auxiliaries

Crushing

Process, Decant & Fresh Water MMG Village

Offices, Workshop & Misc

Transmission Losses

Generation Auxiliaries


10

As only a monthly a predicted load was available, the following hourly loads were

extrapolated from shift knowledge and information provided by Bruce Clare. For more

information on Bruce Clare, see the appendix section 9.5. The graph below illustrates

predicted MMG village daily electricity usage for February and September. Using predicted

daily electricity usage, an hourly load profile was then produced for a year.

Figure 5: MMG village Daily Electricity use assumption for February

Figure 6: MMG village Daily Electricity use assumption for September

0

50

100

150

200

250

300

350

0 5 10 15 20 25 30

kWh

Hours

February

Load

Average

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25 30

kWh

Hours

September

Load

Average


11

3.2.2 CURRENT POWER SYSTEM BACKGROUND

The current power system was investigated and the information obtained is illustrated in

Figure 7 and 8.

As with most mining villages in Australia, the MMG village is connected to the mine‟s power

station via a 22 KV (in the case of MMG village) transmission line. The various generators

used in the power station can be seen in Table 2. The mine site power station consists of five

1.26 MW Deutz gas generators and three 0.7 MW Cummins and two 2.2 MW GM diesel

generators. When under normal operation, it is expected the five Deutz gas generator to be

used and possibly one 0.7MW Cummins diesel generator to assist load fluctuations. The

other diesel generators will be utilised when extra power is required for mill and other device

start up as well as during gas generators maintenance or failure. Figure 8 illustrates the MMG

mine‟s power system and loads. This power system is not owned by Ramelius Resources but

leased from EnGen Ltd. A five year contract was signed and will be renewed if the mine life

is extended beyond that and the deal provided by EnGen is still the most economically viable.

More information on the leasing contract and tariff is available in Table 3. As can be

observed the mine operator is charged two fees - a fixed monthly and variable fee depending

on the amount of diesel and gas used, and energy produced by the power system.

Figure 7: Mount Magnet gold mine power system


12

Table 2: Generators Powering MMG Mine Operations and Village (Cummins Power, 2007)

Number Owner Manufacturer Rating

(MW) Fuel

Maximum

Efficiency

(%)

Minimum

load ratio

(%)

D1 - Cummins 0.7 Diesel unknown 30



D7 Harmony GM 2.2 Diesel unknown unknown

D9 Harmony GM 2.2 Diesel unknown unknown

G2 EnGen Deutz 1.26 Gas 38 30





Figure 8: Mount Magnet gold mine power system and loads


13

Table 3: Mount Magnet gold mine power system leasing associated cost (BEC engineering,

2011)

Specification Information

Agreement length 5 years

Fixed charge 120,000 ($/month)

Deutz charge 120,000 ($/month)

Variable tariff 0.0155 ($/kWh)

Gas cost 0.1175 ($/kWh)

Diesel cost in July 2010 0.94 ($/L)

Heat rate diesel 0.26 (L/kWh)

Diesel inflation rate 2 (%/mth)

Table 4: Power supply information (Matricon, 2011M)

Specifications Information

Supply Three phase

Voltage 240V

Frequency 50Hz

Load Power Factor 0.948 lagging

Maximum Allowable Site Voltage Drop 7%

Actual Site Voltage Drop 6.66%

Installation Type AS/NZ 3000:2007 Commercial


14

3.2.3 IDENTIFICATION OF RENEWABLE ENERGIES AND RESOURCE ASSESSMENT

In this section of the report, the different types of REs available at MM and resource potential

were indentified and assessed respectively. The resource assessment was undertaken using

the methodology illustrated in Figure 9.

Figure 9: Resource assessment methodology used

There are three different types of RE on earth; solar, geothermal and tidal energy. These are

discussed in more depth in this section of this report.

I SOLAR ENERGY

The sun is the closest star to the earth, which is central to our planetary system. The energy

released by the sun is due to nuclear fusion where hydrogen is melted into helium. The

resulting loss of energy due to the conversion of hydrogen into helium is solar energy. It is

RE produced from the sun and abundantly available in many locations on earth. It is available

as radiation or heat. All RE on earth, except for geothermal and tidal, are derived from solar

energy (Kaltschmitt et al. 2007).


15

I.i PRIMARY SOLAR ENERGY

The primary source of solar energy is available as radiation. Figure 10 below, shows that the

solar resource in Australia is excellent. In addition, it can be seen that the annual daily

average solar exposure at Mount Magnet is around 22 Mega Joules per square meter or over 6

kilowatt hours per square meter. Hence, a more in depth investigation of the solar radiation

resource at MM was undertaken below.

Figure 10: Annual daily average solar exposure in Australia (ERIN, 2008)


16

Table 5: Mount Magnet best, worst and average annual mean monthly global solar exposure

from 1990 to 2010 (BOM, 2011)

Month

Mean global solar exposure (kWh/m2) Average

Clearness

Index

Worst

(1994)

Best

(2010)

Average (1990-

2010)

Jan 6.861 8.917 7.981 0.671

Feb 5.972 7.861 7.104 0.642

Mar 4.833 6.806 6.185 0.645

Apr 4.111 5.472 4.790 0.616

May 3.167 4.639 3.915 0.629

Jun 2.722 3.722 3.409 0.621

Jul 3.028 4.056 3.610 0.622

Aug 3.389 4.806 4.534 0.639

Sep 5.000 6.111 5.921 0.669

Oct 6.417 7.611 7.205 0.686

Nov 7.139 8.194 7.940 0.682

Dec 7.833 8.056 8.286 0.685

Average 5.039 6.354 5.907 0.651


17

Figure 11: Predicted load and solar resource seasonal variation comparison over the year

(BOM, 2011 and BEC, 2011)

The following equation was used to compare solar resource with predicted load:

Solar resource (kWh/d) = Monthly daily horizontal solar radiation average x Surface area

With:

Monthly daily horizontal solar radiation average = Corresponding average value (kW/(m2.d))

Surface area = 500 m2

A good solar resource can be assessed by analysing its average daily radiation and clearness

index throughout the year. In general terms a good solar resource would have an average

horizontal daily radiation and clearness index above 5 kWh.m-2

.day-1

and 0.6 respectively.

Average daily horizontal solar radiation in Mount Magnet ranges from 3.4 to 8.3 kWh/m²

with an annual daily average of 5.9kWh/m². Observing the range of the average daily

horizontal solar radiation it can be concluded that the seasonal effect is a factor that needs to

be considered.

Monthly average clearness index daily values rang in Mount Magnet from 0.62 to 0.68 with

an annual daily average of 0.65.

0 500

1000 1500 2000 2500 3000 3500 4000 4500 5000

0 5 10 15

kWh/(d)

Month

Predicted load and solar resource seasonal variation

LOAD

Solar Resource


18

Looking at the clearness index values and the average daily horizontal solar radiation in

Mount Magnet, the solar resource can be rated as „good‟.

I.ii SECONDARY SOLAR ENERGY

Secondary forms of solar energy are available in many types. These are discussed below.

I.ii.a OCEAN THERMAL ENERGY

Ocean thermal energy is the heat energy stored in the ocean‟s top surface layer attained

through solar radiation absorption (Breeze et al. 2009). Mount Magnet is located over 300

kilometres from the coast making this type of energy fairly difficult to access. However, in

the situation where the mining village is located close to the coast, this type of energy should

be taken into consideration.

I.ii.b HYDRO ENERGY

Hydro energy is derived from moving water occurring as a result of the natural water cycles

during evaporation, evapotranspiration and rainfall. A dam is built where water can then be

collected and used when required to produce power (Breeze et al. 2009). This type of RE is

not available at MM. The different information collected to assess the potential of this

resource at MM can be seen in Figure 13 and 14. Using those tools it can be seen that , the

landscape is very flat, no major rivers are present and there is only little rainfall (<300

mm/yr). This makes this energy unavailable for MM.


19

Figure 12: Australia‟s rainfall map (Kuwahata et al. 2010)

Figure 13: MM topographic map (One line represents 20m elevation) (Google Maps, 2011)


20

I.ii.c WIND ENERGY

Wind energy is kinetic energy of the movement of air masses within the atmosphere. Air

motion is the result of different temperatures on the surface of the earth. In this situation,

different air pressures are created, leading air masses to move from higher pressure regions to

lower pressure regions (Patel, 2006). As it can be observed in Figure 15 below, the wind

resource on the South and South West Australian coastline is excellent. Mount Magnet is

located about 300km inland from the South West Australian coast. It is important to mention

that in most cases, the more inland the location, the lower the wind resource. Observing the

figure below, the mean wind speed at 80m above ground level is estimated to be above

6.5m/s at Mount Magnet and can be said to be a „good‟ wind resource. Hence, a more in

depth investigation of the resource at Mount Magnet is undertaken below.

Figure 14: Mean wind speed at 80m above ground level in Australia (ERIN, 2008)

The data used for the below wind investigation was purchased from the Bureau of

Meteorology (BOM). This data consists of 10 minute hourly averages for 2006, 2007, 2008,

2009 and 2010 measured at 10m above ground level at Mount Magnet airport.


21

A few data validation tests were performed to confirm the consistency of the data. First, the

data was screened, where validation criteria were used to highlight suspect values. Then, data

was verified, which consisted in deciding either the suspect value would be kept as valid or

removed.

A range test was undertaken for each parameter. The various range test used can be observed

in Table 6 below.

Table 6: Range test specification (AWS, 1997)

Sample Parameter Range test Comment

Wind speed 0 < average < 25m/s

Minimum: 0 m/s

Maximum: 18.05m/s

1461 values occurred as “error”, hence they were

removed

Wind direction 0 < average ≤ 360˚

Minimum: 1˚

Maximum: 360˚

As 1461 data wind speed were removed their

corresponding wind direction was also removed

The recovery rate was then calculated to assess the relevancy of the collected data:

Recovery rate (%) =

x 100

Recovery rate (%) =

x 100 = 96.66%

The recovery rate is fairly high (96.66%). In addition the topography at MM can be observed

in Figure 14 to be fairly flat. Hence, provided data will be fairly representative of the wind

resource at MMG village.


22


Magnet (BOM, 2011)

Month Wind speed

m/s

January 5.200

February 4.944

March 4.767

April 3.996

May 3.649

June 3.911

July 3.783

August 3.918

September 4.412

October 4.984

November 5.055

December 5.143

Average 4.465


Mount Magnet (BOM, 2011)

3

3.5

4

4.5

5

5.5

0 2 4 6 8 10 12

m/s

Month

Monthly average wind speed at Mount Magnet

Wind speed

Average


23

Figure 16: Long term daily diurnal variation in the monthly average hourly wind speed

for January, April, July and October at 10m above ground surface at Mount Magnet

(BOM, 2011)

Figure 17: Annual average wind rose at 10m above ground level at Mount Magnet in m/s

(BOM, 2011)

2

2.5

3

3.5

4

4.5

5

5.5

6

0.00 5.00 10.00 15.00 20.00 25.00

Win

dsp

eed

(m

/s)

Time (hours)

Long term monthly average hourly windspeed

January

April

July

October

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

1 5 9 13 17 21

25 29

33 37

41 45

49 53

57

61

65

69

73

77

81

85

89

93

97

101

105

109

113

117

121

125 129

133 137

141 145

149 153

157 161 165 169 173 177

181 185 189 193 197 201

205 209

213 217

221 225

229 233

237

241

245

249

253

257

261

265

269

273

277

281

285

289

293

297

301

305 309

313 317

321 325

329 333

337 341 345 349 353 357

12+

9-12

6-9

3-6

0-3


24


(BOM, 2011)


Magnet (BOM, 2011)

Determination of k and c:

To obtain the shape (k) and scale (c) factor for Mount Magnet wind resource the following

was undertaken:

- (1-cumulative probability) was obtained for each bins

- Ln(-ln(1-cumulative probability)) was then calculated for each bins

2.2%

4.2%

16.2%

11.5%

18.8%

16.0%

13.3%

8.8%

5.1%

2.3% 0.8%

0.3% 0.2% 0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

Freq

uen

cy o

f o

ccu

ren

ce (

%)

Wind speed (m/s)

Frequency Histogram of Wind Speed

0%

20%

40%

60%

80%

100%

120%

0 5 10 15

Cu

mu

lati

ve p

rob

abili

ty (

%)

Wind speed (m/s)

Cumulative probability function


25

- Ln(Vx) was acquired for each bins, with Vx being the middle of each bins

- Ln(-ln(1-cumulative probability)) versus ln(Vx) was plotted

- A linear trend line was then fitted


surface

Table 35 in the appendix section 9.2 of this report shows the different steps involved to

produce Figure 21.

The straight line observed in Figure 21 is of the form y = a + bx

Where:

- y = ln(-ln(1-cumulative probability))

- x = ln(Vx)

- a = -kln(c)

- b = k

Here y = a + bx is given as y = -3.0112 + 1.9257x, hence k = 1.9257 and c =

= 4.78

In this situation k = 1.9257 and c = 4.78 m/s

y = 1.9257x - 3.0112

-6

-4

-2

0

2

4

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0

ln(-

ln(1

-cu

mu

lati

ve p

rob

abili

ty))

Ln(Vx)

Weibull distribution factor estimation graph


26

Probability of wind occurrence assessment:

% winds < 3m/s = 22%

% winds > 6m/s = 100% - %winds < 6m/s

= 100% - 69%

= 31%

Figure 21: Load and wind resource seasonal variation comparison over the year (BOM, 2011)

The following equation was used to compare the wind resource with load:

Wind resource (kWh/d) = 0.5 x Air density x sweep area x Coefficient of performance x

Wind speed

With:

Air density = 1.23 kg/m3

Sweep area = 2.3m2

Coefficient of performance = 1

Wind speed: Corresponding monthly average wind speeds (m/s)

1000

1500

2000

2500

3000

3500

4000

4500

5000

1 3 5 7 9 11

kWh/d

Month

Predicted load and wind resource seasonal variation

LOAD

Wind Resource


27

It is observed in Figure 17 above that no matter the period of the year, the wind has a very

similar pattern throughout the day. However it is noticed that monthly average hourly wind

speeds for January are higher than the ones for October, which are higher than the ones for

April and July.

Figure 19 represents the frequency distribution of the wind speed. It is observed that the first

and second highest frequencies of occurrence of wind speeds are between 4 to 5 and 2 to 3

m/s respectively. Very little wind speed occurrence is observed above 12 m/s.

Observing the wind rose (Figure 18), it can be seen that the wind at MM has mainly a East

South East direction. However, the various storms (12+ m/s wind speed) have a North West

direction.

The k value for the wind speed data was obtained to be 1.9257. This k value can be

considered average as it is close to 2. k values around 2 mean that the wind speed of the site

has an average spread around the median (REUK, 2011). In this case, it is observed in Figure

20 that about 22% of the wind speeds is below 3m/s and 31% above 6 m/s. Hence around

47% of the wind is between 3 and 6m/s. Most wind turbines do not operate with wind speeds

below 3 m/s. In addition, optimum wind turbine efficiencies are achieved at wind speeds

above 6 to 8m/s. In the MM case, 22% of the wind resource cannot be harvested. In brief, the

wind resource at this location is fairly good. Hence, wind harvesting for power generation can

be feasible and should be investigated.

I.ii.d BIOMASS ENERGY

Biomass energy is energy stored in materials derived from living organisms. This energy

originates from photosynthesis and includes all plant life, subsequent species in the food

chain and organic wastes. The chemical energy stored in biomass is released as heat. Biomass

is nature‟s way to store solar energy (Breeze et al. 2009). Biomass energy is present at Mount

Magnet and the resource was assessed and discussed below.

Energy derived from biomass is potentially greenhouse neutral, as the carbon dioxide release

during the combustion of the fuel was taken out as the biomass grew. However this does not

take into account the energy use to dry the biomass and transport it where greenhouse gases

are not offset (Breeze et al. 2009).


28

The biomass growth at Mount Magnet is very limited due to very arid weather condition and

poor soil quality. Hence, the development of a biomass field for producing energy for MMG

village would be unlikely to be feasible.

Other resources of biomass were analysed, such as agricultural waste. As it can be observed

in Figure 23, some agricultural areas are located fairly close to MM. Hence this resource

could be available in this situation. An arrangement can be organised between MMG village

power station and the farmers so agricultural waste can be provided and stored. This would

lead to a storage facility to be built as agricultural waste is only seasonal and do not occur all

year around. As it can be seen in Figure 24, railway lines are also present around MM and

could be used to transport the biomass. The feasibility of this option will only be investigated

if BIOMASS technology appears to be interesting for MMG village project.

Figure 22: Land use in Western Australia (Commonwealth of Australia, 2001)


29

Figure 23: Non-urban railway lines covered by WA rail access regime (ERA, 2011)

Figure 24: Western Australia crop production estimates for 2010-2011 (ABARE, 2011)

4700

1300

705 293

0

1000

2000

3000

4000

5000

Wheat Barley Canola Lupins

kt

Winter Crop Production Estimates in Western Australia for 2010-2011


30

I.ii.e WAVE ENERGY

Wave energy is RE produced by wind blown over the surface of the ocean. Energy is then

transferred from the wind to the waves. Even though wave power generation is a relatively

new technology and still quite experimental, a wide range of devices designed to harness this

energy can be found around the world. Nevertheless, Mount Magnet is located over 300

kilometres from the coast making this type of energy fairly difficult to access and so

unviable.

Figure 25: Australia‟s wave resource map (Herman, 2011)

I.ii.f OCEANIC CURRENT ENERGY

Oceanic current energy is kinetic energy of the movement of water masses within the ocean.

This motion of water is generated by wind, breaking waves, the rotation of the earth,

temperature and salinity differences and tides (Breeze et al. 2009). Tidal energy is discussed

later on in this section of the report. As previously mentioned, Mount Magnet is located over

300 kilometres from the coast making this type of energy fairly difficult to access.


31

II GEOTHERMAL ENERGY

Geothermal energy is thermal energy released from the earth. This energy is generated from

the radioactive decay of minerals. The Earth‟s heat flow originates from a combination of the

heat generated during its formation and decay of long-lived radioactive isotopes. The

temperature inside the earth reaches about 7000˚C. This temperature difference between the

core of the earth and its surface produces convective movement of material and heat flow

causing tectonic plates movement, volcanoes and earthquakes. Geothermal energy is present

everywhere on Earth but is not easily accessible (Breeze et al. 2009).

As it can be seen in Figure 27, the ground temperature 5km below ground surface around

MM is around 135˚C. The cost to build such a facility for a small power system (maximum

300 kW) will easily outweigh the economic benefits. Hence, geothermal will not be

considered in this project for the MMG village power system.

Figure 26: Ground temperature at 5km below ground surface in Australia (Ecogeneration,

2011)


32

III TIDAL ENERGY

Tidal energy is generated from planetary gravitation and motion. As the moon rotates around

the earth which rotates around the sun, the mass gravitational effect that they have on each

other causes tide variations and is practically inexhaustible (Breeze et al. 2009). The viability

of this resource on the Western Australian coast is, however, fairly low. In addition, the

resource of such energy is located over 300km from Mount Magnet making it difficult to

access and transport and is, therefore not considered in this report.

Figure 27: 50th

percentile of hourly tidal current speed in meter per second (Griffin et al.

2010)


33

3.2.4 TECHNOLOGY IDENTIFICATION AND SELECTION

The technology selection process was investigated and a Multi-Criteria Analysis (MCA) was

selected for this application.

Several technology selection processes were investigated and assessed as to whether or not

they were suitable for this project. It was found that the two most appropriate selection

methods were a multi-criteria analysis or an Environmental and Economic Sustainable

Assessment (EESA).

EESA provides a quantitative, objective and rational method of measuring each relevant

social, environmental and economic criterion that must be included in decision making. This

is achieved by allocating each criterion with a unitary monetary value (Hardisty, 2009)

Even though EESA selection principles seemed the most appropriate selection method to use

for this project, it was found to be too time consuming and resource-demanding for the

purpose of this project.

The MCA of the different technologies available were undertaken using the steps outlined

below:

1. Identification of criteria and stakeholders

2. Criteria weighting

3. Option identification and rating

1. Identification of criteria and stakeholders

Initially, the criteria to be used in the MCA for the selection of the appropriate technology for

harvesting solar and wind energy were identified. The selection was done by using the Triple

Bottom Line (TBL) approach, with criteria selected from Social, Environmental and

Economic fields. The Global Reporting Initiative‟s G3 guidelines were also used to obtain

some of these criteria. The selected criteria can be seen in Table 8 below.


34

Table 8: Selected Social, Environmental and Economic Criteria for MMG village RE power

system (Hardisty, 2010 and Wang et al. 2009)

Social Environmental Economic Technical

- Education on use

- Health and safety

- Employment

- Social

acceptability

- Social benefits

- Materials use

- Energy use

- Biodiversity

- Emissions

- Compliance

- Land use

- Aesthetic

- Capital cost

- Operating cost

- Efficiency

- Reliability

- Maturity

- Implementation

duration

Then stakeholders whose interests would be affected by the implementation of this project

were identified. These were found as followed:

Table 9: MMG village RE power system project stakeholders

Identified Stakeholders

- Head office

- MMG village employee

- MMG village resident

- MM community (resident)

2. Criteria weighting

The selected criteria and stakeholders were then used to obtain appropriate weightings for

each criterion. A rating from 0 to 10 according to the importance of each criterion depending

on the stakeholders was performed with 0 and 10 being of lowest and highest importance

respectively. A scale factor of 10 was given to the head office and 3, 2 and 1 for MMG

village employees, MMG village shift workers and MM residents respectively. The result of

this task can be observed in Table 39 in the appendix 9.4 section of this report.


35

3. Option identification and rating

Solar Radiation:

In this situation, it is required to convert solar energy into electricity. The conversion of solar

power can be done using two types of technology; Photovoltaic (PV) and Concentrated Solar

Power (CSP). Biomass power systems were also taken into consideration.

Wind:

To convert wind energy into electricity, several devices are available. Wind turbines are used

to convert the wind kinetic energy into mechanical energy. This mechanical energy is then

converted into electrical energy using a generator. The two main types of wind turbine used

around the world are horizontal and vertical axis wind turbines (Kreith et al. 2007).

Horizontal axis wind turbines (HAWT) are more common than vertical axis‟ ones. These

wind turbines have a horizontal orientated shaft, which helps the conversion of the wind

energy into rotational energy. Electrical components as well as the generator are installed at

the top of the tower. There are many different types of HAWT. They differ depending on the

number of blades used, sweeping area, tower height, turbine position (upwind or downwind),

generator size, electrical component used (gearbox or gearless), control systems etc (Ibid).

Vertical axis wind turbines have vertically orientated shafts. These have few advantages over

the horizontal ones. Electrical components such as gearbox and generator can be installed at

the base of the tower lowering system stabilizing structure requirements and improving

access for maintenance purposes. In addition, these types of wind turbines operate better in

turbulent wind locations. However, they have a smaller sweeping area, lowering their wind

energy harvesting possibility. Moreover, these wind turbines are not self-starting machines

and require to be started in motoring mode and then switched to generating mode. These

wind turbines are mostly used in high variable wind direction location (e.g. urban) (Ibid).

Wind turbines can be categorised into three groups; small, medium and large. Small wind

turbines are less than 20kW. They are used for residential purposes and designed with low

cut-in wind speeds (between 3 to 4 m/s). Medium wind turbines have a 20 to 300 kW

capacity. These are mostly used to supply power to remote areas‟ loads or commercial

buildings. Large wind turbines are in the MW power range. These turbines are mostly used

for wind farm purposes (Ibid).


36

Summary:

Three types of renewable energies were assessed and found good or available at MM. These

included solar radiation, wind and biomass. The different technologies available to harvest

these energies were identified and assessed. For harvesting solar radiation, the technologies

identified were, photovoltaic (PV), concentrated photovoltaic (CPV) and solar thermal.

Various types of biomass and solar thermal are available but they mostly have similar

characteristics, hence they were treated as a whole for each resource. The different options

available to harvest wind energy were also identified. As in this situation the most

appropriate option was fairly clear, no decision methodology was undertaken. It was found

that horizontal axis wind turbines would be more favourable over the vertical axis ones at

MMG village.

As it can be seen in Table 10, PV is the best option for this project, wind second,

concentrated PV third, solar thermal fourth and biomass last. The overall calculations and

rating of the different options can be seen in Table 41 in the appendix 9.4 section of this

report.

Table 10: MCA final outcome

Option Total rating Rank

Wind 3.8112 2

PV 3.8146 1

Solar Thermal 3.2254 4

Biomass 3.2110 5

Concentrated PV 3.2529 3

3.2.5 RE POWER SYSTEM ANALYSIS

One of the main aims of this project is to assess the potential of RE in the current power

system and in the case of a standalone system. At first, it was decided to use HOMER to

undertake this task. HOMER is an energy modelling software used internationally to assess

and size hybrid RE power systems. More information about HOMER is provided later on in

the report. However, after investigating the current village‟s power system, it was decided to

specifically design an Excel spreadsheet to acquire the appropriate economic RE mix for

MMG village as HOMER was not suited for this application. This Excel spreadsheet will be


37

referred to as REMAX in this report. More information on REMAX is provided in this

section below. In the situation where standalone energy modelling was required, HOMER

was used.

While investigating the current power system, it was found that the retrofit of RE to offset

carbon emissions of the village would have very small to no impact on the current power

system. This is due to the large size of the power system (≈7MW) and the small proportion of

energy used by the village (2.46%). This has to do with the sensitivity of the power system to

modify its fuel consumption according to the load. Power system engines such as the one

used at MMG mine operate at a constant rotational speed. More fuel is used when the load is

increased and vice versa. It is believed that the sensitivity of the MMG mine‟s power system

is in the range of 50 to 100 kW. Hence, a load fluctuation of several kilowatts would not

affect the energy consumption of the power station engines. In this situation, only a small

fraction of the RE produced from the retrofitted RE substation will penetrate the system,

making it unfeasible. For this study, this is unfavourable as the embodied energy of the

village would be increased and no or little reduction in operational energy observed. To

increase the feasibility of RE power systems, the penetration of energy produced by the

system must be maximal. In the section where the potential of RE in the current power

system is investigated, it was assumed that the mine‟s power system operates ideally. This

means that if the load varies by 0.01 kW or more, the fuel consumption of the generators

would be adjusted.

The methodology followed to investigate the potential of a RE in the current power system

and in the case of standalone is as followed:

I IDENTIFY THE DIFFERENT SYSTEM CONFIGURATIONS

I.i CURRENT POWER SYSTEM

Single source as well as hybrid systems were analysed.

It was decided to study with REMAX the feasibility of the following configuration

within the current power system:

o Mine‟s Power System (Current system)

o Mine‟s Power System + Wind turbine(s)

o Mine‟s Power System + PV array + Inverter

o Mine‟s Power System + PV array + Inverter + Wind Turbine(s)


38

In this situation, no battery was required as the MMG village‟s power system would behave

as a small grid connected system. Hence, the mine‟s power system would be used as backup

when required.

I.ii STANDALONE

The feasibility of the following standalone system configurations were undertaken

using HOMER:

o Generator(s)

o Generator(s) + Wind turbine(s)

o Generator(s) + PV array + Inverter

o Generator(s) + PV array + Inverter + Wind Turbine(s)

It was decided not to include any battery back-up in the standalone system. This decision was

made to reduce the Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) of

the system. In addition, batteries tend to lower the overall system efficiency. Hence, it was

decided to use low load diesel generators so batteries would not be needed and the RE

penetration into the system maximum.

Because there is no access to the natural gas pipeline near the village, it was decided to use

Diesel as a source of energy for the generator. Low load diesel generator manufacturers were

researched and REGEN Power was found to provide a very appropriate product for the

standalone situation. Hence, information provided by Chem Nayar during a meeting about

REGEN power technology was used in the modelling of the generator in HOMER.

REGEN Power came up with an electronic component that can be added to almost any type

of generators. For the moment, the maximum size of generator they can work with is around

250kW, but they are predicting to work with bigger generators fairly soon. This electronic

component allows the generator to run at very low load (5% of maximum capacity) and

almost maintain its maximum efficiency at any load. These types of generators lead to major

savings in energy and increased RE penetration in the system.


39

II INPUT OF DATA IN THE MODELLING SOFTWARE

The different information used to model the potential of RE in the current power system and

as a standalone system can be seen in Table 11 to 15 and Figure 29 to 32 below.

It is important to mention that for the PV array size, various sizes were investigated. Even

though the size of the PV array was modified the other information, such as cost, was kept

the same. No PV array below 50 kW was investigated as the cost used in this study is only

relevant for PV array size above or equal that value.

Table 11: Project information inputs

Project Information

Properties Unit Value

Project Lifetime yrs 8

Discount rate % 8%

Latitude Degrees -28

Longitude Degrees 116

Standard time longitude Degrees 120

Carbon Price $/t(CO2) 23

Table 12: REMAX: Project information inputs

Project Information

Properties Unit Value

Diesel inflation rate %/mth 2%

Diesel carbon content t(CO2)/L 0.002683

Gas carbon content t(CO2)/m3 1.99E-03

Carbon Price Inflation rate %/yr 3%

LTCs cost (RECs) $/MWh(RE) 40

Load factor (Compared to MMG village)

1

The calculations undertaken to calculate the gas and diesel carbon content is available in the

appendix section 9.7 of this report.


40

Table 13: REMAX: Generator information inputs

GENERATOR

Properties Units Value

Gas cost $/kWh 0.1175

Diesel cost $/L 1.1092

Diesel to gas

ratio % 13%

Heat rate diesel L/kWh 0.26

Fixed charge $/yr 72324

Variable charge $/kWh 0.0155

Gas turbine eff % 36%

Gas energy

content MJ/m3 38.7

Figure 28: HOMER: Generator input screen shot 1


41

For the PV array, the information used was taken from background knowledge and several

manufacturers. The cost of the PV array installed was estimated from several manufacturers

and the overage cost of around 4250 $ per kilowatt installed was used for this analysis. More

information on the assumptions made for this estimation is available in the appendix section

9.7 of this report. Figure 30 and 31 illustrate the solar resource on different surface tilt angles

seasonal variation and their annual average respectively. As it can be seen, the surface

equipped with a tracking system and tilted at latitude angle (28˚) has the highest and the

second highest annual average respectively. When compared to the load it can be observed

that having a tracking system or not would not make a large difference. Hence, it was decided

to use a fix PV array tilted at the latitude angle (28˚).

Figure 29: Load and solar resource on different surface tilt angles seasonal variation

comparison at MM (NASA, 2011).

Figure 30: Annual average solar resource on different surface tilt angles at MM (NASA,

2011)

1000

2000

3000

4000

5000

1 6 11

kWh/d

Month

Solar resource on different surface tilt angles and load seasonal

variation

Tilt 0

Tilt 13

Tilt 28

Tilt 43

Tilt 90

Load

5.71 6.02 6.08

5.81

3.36

6.45

3

4

5

6

7

Tilt 0 Tilt 13 Tilt 28 Tilt 43 Tilt 90 Tracking

kWh/(m2.d)

Surface tilt angle (Degrees)

Annual Average


42

Table 14: PV information inputs

PV Inputs

Properties Units

PV1 PV2

Value

Slope degrees 28

PV array size kW 50 200

Inverter efficiency % 96% 96%

Dust coefficient % 98% 98%

Manufacturing

coefficient % 95% 95%

Temperature

coefficient % 85% 85%

Capital cost $/kW 4250 4250

O and M cost $/yr 0 0

Module lifetime years 20 20

Replacement cost $/kW 3500 3500

Azimuth of surface degrees 180

Ground reflectance % 20%

Table 15: Four Wind Seasons 50 and 100 kW wind turbines information inputs (WT: Wind

Turbine and FWS: Four Wind Seasons)

Wind Turbine Inputs

Unit WT1 WT2

Name

FWS FWS

Capacity kW 100 50

Capital cost for 1, including

everything $/WT 390000 205000

Capital cost for 1 extra turbine $/WT 312000 164000

O and M cost per turbine $/(yr.WT) 19500 10250

Life time yrs 20 20

Hub height m 32 24


43

For each wind turbines investigated in this project, the corresponding power curve was used.

Only 10 wind turbines were investigated as no other manufacturers provided appropriate cost

estimations for their products. The assumptions made to estimate the installed cost of each

wind turbine were assisted by Antony Piccinini. Other wind turbine input information is

available in the appendix section 9.7 of this report. The ten wind turbines investigated in this

project are listed below from smallest to largest:

- Skystream (2.4kW)

- Evance (5kW)

- Gilong (10kW)

- Gaia (11kW)

- WestWind (20kW)

- Four Wind Seasons (FWS) (50kW)



- Enercon (E) (330kW)

- Enercon (E) (600kW)

Figure 32 below illustrates the cost of each wind turbine investigated per installed Watt

versus their capacity. It can be observed that the bigger the wind turbine the lower the cost

per installed Watt.

Figure 31: Cost per installed Watt versus wind turbine capacity.

0

2

4

6

8

10

12

0 100 200 300 400 500 600

Cost ($/W)

Wind Turbine capacity (kW)

Cost per installed Watt versus wind turbine capacity


44

III RE POTENTIAL CURRENT POWER SYSTEM

As mentioned previously, REMAX was used to undertake this section of the project.

REMAX was developed due to HOMER‟s limitations to model the current power system at

MM and other mine sites. Some of the different aspects limiting the use of HOMER for this

section of the project are highlighted below:

- Diesel/Gas generation ratio: It is not possible in HOMER to model a generator

meeting 80% (for example) and another one 20% of the load at the same time. Most

recent mine sites are mainly powered using gas turbines as gas is fairly cheap and

produce less carbon emission than diesel. However, diesel generator are still being

used to meet load fluctuation and in case of emergency.

- Large wind turbine control system: It is not possible in HOMER to model large wind

turbine and limit their output power to load requirements. This is done as larger wind

turbines are cheaper than smaller ones and can be very feasible in low wind speed

regions.

- Limited modelling control: It is not possible in HOMER to modify the way HOMER

models the different systems.

- Long simulation period when assessing several configurations at once.

Table 16, shows the different input required to use REMAX. The different outputs are also

presented.

Table 16: REMAX input and output information

INPUTS OUTPUTS

Project

- Project life time (yrs)

- Discount rate (%)

- Diesel inflation rate (%/mth)

- Diesel inflation rate (%/yr)

- Latitude and longitude (Degrees)

- Standard time longitude (Degrees)

- Diesel carbon content (t(CO2)/L)

Generator only:

- CAPEX ($)

- OPEX ($/yr)

- Total NPC ($)

- Power cost ($/kWh)

- Diesel use (L/yr)

- Generator operation


45

- Gas carbon content (t(CO2)/m3)

- Carbon price ($/t(CO2))

- LTCs cost ($/MWh(RE))

- Load factor (Compare to MMG village)

(hrs/yr)

- Carbon emission

(t(CO2)/yr)

PV:

- CAPEX ($)

- OPEX ($/yr)

- Total NPC ($)


- RE fraction (%)

- Diesel use (L/yr)


(hrs/yr)

- Excess Power (kWh/yr)

- Ratio of excess power to

power produced by RE

(%)

- Carbon emission

(t(CO2)/yr)

Wind Turbine:

- CAPEX ($)

- OPEX ($/yr)

- Total NPC ($)


- RE fraction (%)

- Diesel use (L/yr)


(hrs/yr)

- Excess Power (kWh/yr)

- Ratio of excess power to

power produced by RE

(%)

- Carbon emission

(t(CO2)/yr)

Generator

- Gas cost ($/kWh)

- Diesel cost ($/L)

- Diesel to gas ratio (%)

- Heat rate diesel (L/kWh)

- Fixed charge ($/yr)

- Variable charge ($/kWh)

- Gas turbine efficiency (%)

- Gas energy content (MJ/m3)

PV

- Slope (Degrees)

- Inverter efficiency (%)

- Dirt coefficient (%)

- Manufacturing coefficient (%)

- Temperature coefficient (%)

- Capital cost ($/kW)

- O&M cost ($/yr)

- Module lifetime (yrs)

- Replacement cost ($/kW)

- Azimuth of PV array (Degrees)

- Ground reflectance (%)

- Two PV array size to be considered

(kW)

- Monthly solar resource (kW/(m2.d))

Wind

Turbine

- Two wind turbine capacity (kW)

- Capital cost ($/WT)

- Replacement cost of 1 WT ($/WT)

- O&M cost per turbine ($/(yr.WT))

- Life time (yrs)

- Hub Height (m)

- Wind turbine Power curve

- Hourly wind speed for 1 year (m/s)

- Height of measured wind speed (m)

- Shear exponent


46

III.i REMAX VALIDATION AND LIMITATIONS

Validation:

The following tables compare REMAX output with the predicted information obtained from

the BEC Engineering report and HOMER‟s outputs.

Table 17: REMAX‟s outputs validation for current power system for 2012

Characteristics Provided data REMAX Difference (%)

CAPEX ($) 0 0 0.00

OPEX ($) 244858.63 243935.45 0.38

Diesel use (L) 36808.20 36659.75 0.40

Diesel cost ($/year) 44332.11 44208.13 0.28

Gas cost ($/year) 111323.03 110874.04 0.40

Electricity cost ($/kWh) 0.2248 0.2252 0.18

Overall cost ($) 244858.63 243935.45 0.38

Table 18: REMAX‟s PV and wind turbine outputs validation with HOMER

Output (kWh/yr) Difference

(%) HOMER REMAX

PV array size (kW)

50 92623 95607.5 3.1216%

100 185246 191215 3.1216%

150 277868 286822.5 3.1220%

200 370491 382430 3.1219%

250 463114 478037.5 3.1218%

300 555737 573645 3.1218%

Wind turbine number

FWS100 x 1 272225 265630 -2.4828%

FWS100 x 2 544450 531260 -2.4828%

FWS100 x 3 816675 796890 -2.4828%

Other

Estimated Horizontal

radiation (kWh/yr) 2153.496 2153.91 0.0192%


47

Table 18 compares different sizes of PV arrays and output of different wind turbine

configurations over a year between HOMER and REMAX. It can be observed that the PV

array and wind turbine output difference is around 3% and 2.5% respectively. HOMER is

internationally used software to model and size RE hybrid systems. It has been certified and

validated using real life data. Hence, showing that he difference between REMAX and

HOMER is small will show the accuracy and relevancy of REMAX output information

(HOMER, 2011).

The difference in the PV array and wind turbine outputs over a year compared with HOMER,

can probably be explained due to the accuracy of the different algebras used to calculate the

solar incidence on the PV array for each hour over a year in REMAX. In addition, HOMER

models fluctuation on a daily basis of the solar radiation, which is not done in REMAX. This

would definitely lead to some differences.

As it can be observed in Table 17 above, the differences between the predicted costs of the

current power system and outputs from REMAX are very small (<0.4%). In addition, when

REMAX‟s outputs are compared with HOMER‟s output for different PV array size, it can be

seen in Table 18 that the differences are very small too (<3.122%). Hence, increasing the

relevancy of REMAX‟s output information.

Limitations:

REMAX has several limitations due to little time available to devote to software design.

These are listed and explained below:

- Only models PV arrays and wind turbines as RE power systems.

- PV array configuration number: Only two PV array configurations can be analysed at

once.

- Wind turbine configurations: Only two types of wind turbines can be modelled at

once. In addition each wind turbine is limited to three configurations (1, 2 and 3 of the

modelled wind turbine).

- PV array + Wind turbine + Current power system configuration: Only one

configuration of this system can be analysed at once.

- Ideal current power system: For this study, REMAX considers that the mine power

system is ideal and load fluctuation is sensible to a figure of 0.1 Watts. This can be

modified in a future version of REMAX.

- Not user friendly.


48

III.ii RESULTS AND ANALYSIS

Each different configuration mentioned previously was investigated for several project lives

(1 to 18 years). For the PV array and wind turbine(s) several different sizes and varying

numbers of them were analysed by the modelling software so the most appropriate one

depending on the resource as well as the ongoing and capital cost could be identified. The

configuration with the lowest Net Present Cost (NPC) could then be identified. The system

with the lowest NPC is the system that is the most economically viable.

As mentioned previously, the current power system‟s sensitivity is believed to be around 50

to 100 kW. Hence, a curve was plotted (Current Power System (80% Ideal)) to represent

where the system NPC would lie with different project lifetimes. It is important to mention

that this curve was estimated. This information was investigated, but it was found that more

research and monitoring was required, which was beyond the scope of this project.

III.ii.a WIND TURBINE SELECTION

To select the appropriate wind turbines to be considered in the RE mix, the ten selected wind

turbines were modelled in REMAX. The different outputs used to undertake this section is

available in the Appendix section 9.7.

It was decided to select only the four most appropriate wind turbines due to the limitation of

REMAX to be able to model only two wind turbines at a time. Looking at Figure 33, it can be

seen that the four most appropriate wind turbines for this project are the Four Wind Seasons

(FWS) 50, 100 and 200 kW and Enercon (E) 330 kW. These wind turbines will provide the

most significant offset of carbon emissions with minimum NPC difference with the current

power system.


49

Figure 32: NPC difference with current power system per ton of CO2 emissions offset (Project life of 9 years)

0.0E+00

5.0E+03

1.0E+04

1.5E+04

2.0E+04

2.5E+04

3.0E+04

3.5E+04

4.0E+04

($)

System configuration

NPC difference with current power system per tonne of CO2 emissions offset


50

III.ii.b WIND TURBINE(S) + PV ARRAY + CURRENT POWER SYSTEM SELECTION

To select the most appropriate system configuration, the same method as when selecting the

wind turbines was used. . Figure 34 illustrates the NPC difference with the current power

system per tonne of CO2 emission offset for a project life of 8 years. Hence, it can be

observed that the most suitable system configurations for this case is a 50 kW PV array with

one and two 100kW FWS wind turbines, 200 and 330kW PV array with one FWS wind

turbine. These configurations were then used to assess the economic viability of these

systems under different project lives.

Figure 33: NPC difference with the current power system per tonne of CO2 emissions offset

(Project life of 8 years)

III.ii.c ANALYSIS

As it can be observed in Figure 35 below, retrofitting RE power systems with the current

power system begins to be economically viable if the project life is 13 years or more.

0

500

1000

1500

2000

2500

($)

System configuration

NPC difference with the current power system per tonne of CO2 emission offset


51


2012 with different project life.

Future potential of RE in the current power system was also analysed for a project starting in

2014, 2016 and 2018. In this situation, the cost of PV was calculated using estimations and

can be observed below. In 2010, the IEA projected decrease in the capital cost of PV of 40%

between now and 2015 and 50% by 2020 (Hearps et al. 2011). Figure 36 represents the

projected installation cost of PV per rated kW. The projected cost of each investigated wind

turbine was also calculated using estimation and can be observed below. In 2010, the IEA

projected a decrease in the capital cost of wind power of 17% between now and 2030 (Hearps

et al. 2011). Figure 37 represents the projected installation cost of the investigated wind

turbines. The projected cost of diesel and carbon price was also investigated and the

assumptions made can be observed below.

For a project starting in 2014, 2016 and 2018, where the cost of the RE power system is

predicted to decrease and cost of diesel increase, the retrofitted RE power system begins to be

economically competitive with the current power system, if the project life is 9, 7 and 6 years

respectively. These retrofitted RE power systems only become economically feasible if the

0

0.5

1

1.5

2

2.5

3

1 3 5 7 9 11 13 15 17

NP

C x

1,0

00,0

00 (

$)

Project life (years)

NPC analysis (Starting January 2012)

Current Power System (Ideal)

Current Power System (80% Ideal)

Current Power System (Ideal) + RE


52

current power system is assumed to be ideal. In the actual situation observed when the current

power system is assumed to be 80% ideal, refitting RE in the power system would not be

economically viable. Hence, the potential of retrofitting RE power systems in the current

power system is zero. In this situation, no further investigation was undertaken.

The individual analysis of each power system for different project lives can be observed in

the appendix section 9.7 of this report.

Figure 35: Projected installed PV cost

Cost of installed PV use:

2014: -566.67 x 2014 + 1144383 = 3110 $/kW

2016: -85 x 2016 + 173825 = 2465 $/kW

2018: -85 x 2018 + 173825 = 2295 $/kW

y = -566.67x + 1E+06

y = -85x + 173825

1500

2000

2500

3000

3500

4000

4500

2010 2012 2014 2016 2018 2020 2022

($/kWp)

Year

Projected installed PV cost

2015 forecast

2020 forecast

Linear (2015 forecast)

Linear (2020 forecast)


53

Figure 36: Projected installed wind turbine cost

Table 19: Projected installed cost of the investigated wind turbine

Installed wind turbine cost ($)

Years FWS

50kW

FWS

100kW

FWS

200kW

E

330kW

2012 204999 390000 740000 1153000

2014 201127 382633 726022 1131222

2016 197255 375267 712044 1109444

2018 193383 367900 698066 1087666

2030 170150 323701 614200 956998

Cost of Diesel use:

2014: Diesel cost: June 2012 cost x (1 + 0.08)2014-2012

= 1.20 x (1.08)2 = 1.40 $/L


= 1.20 x (1.08)4 = 1.64 $/L


= 1.20 x (1.08)6 = 1.91 $/L

y = -1936.1x + 4E+06

y = -3683.3x + 8E+06

y = -6988.9x + 1E+07

y = -10889x + 2E+07

0

200000

400000

600000

800000

1000000

1200000

2010 2015 2020 2025 2030 2035

Inst

alle

d c

ost

($)

Year

Projected installed wind turbine cost

FWS 50

FWS 100

FWS 200

E 330


54

Carbon price use:

2014: January 2012 Carbon price x (1 + 0.03)2014-2012

= 23 x (1.03)2 = 24.4 $/t(CO2)


= 23 x (1.03)4 = 25.9 $/t(CO2)


= 23 x (1.03)6 = 27.46 $/t(CO2)



0

0.5

1

1.5

2

2.5

3

3.5

1 3 5 7 9 11 13 15 17

NP

C x

1,0

00,0

00 (

$)


NPC analysis (Project starting January 2014)





55





0

0.5

1

1.5

2

2.5

3

3.5

1 3 5 7 9 11 13 15 17

NP

C x

1,0

00,0

00 (

$)



Current Power System (Ideal) Current Power System (Ideal) + RE Current Power System (80% Ideal)

0

0.5

1

1.5

2

2.5

3

3.5

4

1 3 5 7 9 11 13 15 17

NP

C x

1,0

00,0

00 (

$)







56

IV RE POTENTIAL IN A STANDALONE POWER SYSTEM

IV.i HOMER

HOMER was used to acquire the appropriate economic RE mix for MMG village‟s

standalone power system. HOMER model the operation of each requested system

configurations for each hour in a year (8760 hours) by making energy balance calculations.

For each hour, HOMER compares the load demand with the energy that each different

system configurations can supply (HOMER 2011).

For the PV array, Inverter and Wind turbine(s) several sizes and quantities were analysed by

the modelling software, so the most appropriate configuration depending on the resource as

well as the ongoing and capital cost could be identified.

Only the four wind turbines selected to be investigated for assessing the potential of RE in the

current power system were used in this section.

To undertake this section, firstly the most appropriate standalone diesel power system was

determined using HOMER and then used for the rest of the RE analysis.

Before undertaking the analysis, the appropriate diesel generator system had to be selected.

This was performed using HOMER by modelling a select variety of different sizes of diesel

generators. The one used was the most economically viable. This system is composed of

three ENGEN Power low load diesel generators, a 150, 100 and 50 kW.

IV.ii RESULT AND ANALYSIS

- Project starting January 2012 with a sensitivity analysis on the project life:

Figure 41 shows that no RE power systems would be competitive with the selected diesel

generators if the project life is 6 years or less. However, for project lives above 6 years, the

most economically viable configuration is two or three FWS 100kW wind turbines combined

with the selected diesel generators. The most economically viable system configuration

depending on the project life can be seen in Table 20 below.


57


load cycle REGEN Power generators (150kW + 100kW + 50kW))

Project

life (Yrs)

Standalone system

configuration Total NPC ($)

Renewable

energy

penetration (%)

CO2 offset

(t/yr)

1 Generators $476,201.00 0% 0.00

2 Generators $804,656.00 0% 0.00

3 Generators $1,109,265.00 0% 0.00

4 Generators $1,390,469.00 0% 0.00

5 Generators $1,651,141.00 0% 0.00

6 Generators $1,891,891.00 0% 0.00

7 Generators + FWS(100kW) x 2 $2,084,466.00 51% 216.53












Figure 41 below illustrates the NPC of the standalone and current power system located at 2,

4 and 6 kilometres away from the village for different project lives. In the case of the

standalone power system, only the NPC of the most economically feasible system for the

different project lives was used .This was done by adding the cost of the transmission line to

connect the mine power system with the village. After meeting up with Antony Piccinini

from WorleyParsons and Bruce Clare from BEC Engineering, it was learned that a variation

in the size of the line only led to small variation in the cost of the transmission line. A rough

estimation of the cost of the transmission line was also provided by Antony Piccinini and

estimated to be around $250,000 per kilometre for a 22 KV line with steel posts. The


58

transmission line connecting MMG village with the mine‟s power station is a 22 KV line.

Hence this estimation was used to produce the figure below.

Observing Figure 41, it can be seen that if the mine‟s power system is located less than 2

kilometres away from the village and if the project life is higher than 2 years, the current

power system would be more economically viable. However, if the mine‟s power system is

located over 4 kilometres away from the village, the standalone configuration would always

be more economically viable.

Figure 40: NPC analysis comparison of the standalone and current power system located at 2,

4 and 6 kilometres away from the village for different project lives (Transmission line cost:

$250,000 per km)

Figure 42 compares the carbon emissions per year of the standalone and current power

system. It is important to mention that this graph only represents the operational carbon

emissions. The embodied energy of the transmission line and generators associated with the

different system is not included in the analysis.

It can be observed that for the project lives (1 to 6) where the standalone power system

operates with the selected diesel generators only, the carbon emission is higher. This is due to

0.5

1

1.5

2

2.5

3

3.5

4

1 3 5 7 9 11 13 15 17

NP

C x

1,0

00,0

00 (

$)


Standalone and current power system NPC analysis for different transmission line length

Current Power System (6 kms)



Standalone Power System (Generators only)

Standalone Power System (Generators + RE)


59

the efficiency of the generators. As mentioned previously, larger generators (In the case of

the current power system) are more efficient than smaller generators (Standalone situation).

In addition the carbon content of diesel is higher than gas. 87 percent of the power generated

is from gas and 13% from diesel in the current power system. Hence, to produce the same

amount of energy (1.09 GWh), a diesel only generator power system would produce more

carbon emissions, which can be observed in this situation. Nevertheless, once the project life

if high enough (7 years or more), and the RE power system becomes competitive in the

standalone situation, the carbon emission per year is well below the current power system.

Figure 41: CO2 emissions comparison for a project starting in January 2012

- Project starting in January 2012 with a sensitivity analysis on PV cost and project life:

Figure 43 below, represents the most favourable system under different conditions. The X

axis represents the multiplier of PV installed cost (0 to 1) and the Y axis, the project life (5 to

18 years).

This analysis was undertaken using HOMER to assess when PV power systems become more

economically viable than the FWS 100 kW wind turbine at MM. Analysing Figure 43 it can

200.00

300.00

400.00

500.00

600.00

700.00

800.00

0 5 10 15 20

t(C

O2)

/yr

Project life (yrs)

C02 emissions comparison (Project starting January 2012)

Current power system

Standalone power system (GEN)

Standalone power system (GEN + RE)


60

be seen that if the PV cost is half of what was assumed (

= $2125 per kW installed) and

the project life is below 11 years, “PV + Generators” system would be the most economically

viable system. However, if the cost of PV is more than 0.7 time the cost assumed (4250 x 0.7

= $2975 per kW installed) and the project life more than 7 years, the “Wind turbine +

generators” system configuration seems to be the most appropriate one. Nevertheless it can

be seen that the most suitable system configuration for a project life less than 7 years and

with a PV cost higher than 0.8 time the cost assumed (4250 x 0.8 = $3400 per kW installed),

is “generator only”.

Figure 42: HOMER output screen shot for project starting in January 2012 with sensitivity

analysis on PV cost and project life


In a standalone situation, using projected installed wind turbine and PV array costs for

January 2014, it can be observed in Table 21 that a mix of a few of the FWS 100 kW wind

turbines with the selected diesel generator is more economically viable than the diesel

generator system itself with a project life of 5 years or above. It is also seen that the longer

the project life, the more FWS 100 kW wind turbine become viable.


61



Project

life (Yrs)

Standalone system

configuration Total NPC ($)

Renewable energy

penetration (%)

CO2 offset

(t/yr)

1 Generators $550,617.00 0% 0.00

2 Generators $948,257.00 0% 0.00

3 Generators $1,316,725.00 0% 0.00

4 Generators $1,657,454.00 0% 0.00
















62



In this situation, in analysing Table 22, it can be noticed that the most appropriate RE hybrid

standalone power system is a 110 kW PV array with the selected generators for a project life

of 4. Nevertheless, it is only for a project life of 4 years that PV is more appropriate than the

FWS 100 kW wind turbines. It is observed that with increasing project lives, the number of

FWS 100 kW wind turbines becomes higher.

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

0 5 10 15 20

t(C

O2)

/yr

Project life (yrs)






63



Project

life (Yrs)

Standalone system

configuration Total NPC ($) RE penetration (%)

CO2 offset

(t/yr)

1 Generators $610,119.00 0% 0.00

2 Generators $1,062,968.00 0% 0.00

3 Generators $1,482,423.00 0% 0.00

4 Generators + PV(110kW) $1,811,754.00 20% 13.37
















100.00

300.00

500.00

700.00

900.00

1 6 11 16

t(C

O2

)/yr

Project life (yrs)

C02 emissions comparison (Project starting January 2016) Current

power system




64


In this situation, very similar observations as a project starting on January 2014 were made.

The only difference is that the number of FWS 100kW wind turbines increased more with

the project life than in a project starting on January 2016. In addition, the most appropriate

RE hybrid standalone power system is also a 110 kW PV array with the selected generators,

but for a project life of 3 instead of 4 for 2016.



Project

life (Yrs)

Standalone system

configuration Total NPC ($) RE penetration (%)

CO2 offset

(t/yr)

1 Generators $676,912.00 0% 0.00

2 Generators $1,191,611.00 0% 0.00

3 Generators + PV(110kW) $1,628,421.00 20% 13.37

















65


V ANALYSIS SUMMARY

As it was observed in the assessment of the potential of RE power systems in the current

power system and in a standalone situation, the FWS 100kW wind turbines was found the

most appropriate one for this project. More investigation was undertaken to explain this

reason. As it can be observed in Figure 47 and 48, the FWS 100 kW„s power curve is the

same as the FWS 200 kW wind turbine for wind speed below 4 m/s. This would definitely

explain the reason why in this analysis the FWS 100 kW wind turbine appears to be the most

favourable option.

Figure 46: Investigated wind turbines‟ power curves comparison

100.00

200.00

300.00

400.00

500.00

600.00

700.00

800.00

0 5 10 15 20

t(C

O2)

/yr

Project life (yrs)





0

100

200

300

0 5 10 15 20

Ou

tpu

t p

ow

er (

kW)

Wind speed (m/s)

Investigated wind turbines' power curves comparison

Enercon 330kW

Four Wind Seasons 50kW


66

Figure 47: Investigated wind turbines‟ power curves comparison (Zoomed in view)

A potential location for the RE power system at MM was identified and can be seen in Figure

49. Nevertheless, the partial or entire integration of the system within the village

infrastructures should still be considered.

Figure 48: MMG village and possible RE power system location at Mount Magnet

0

10

20

30

40

50

60

2 2.5 3 3.5 4 4.5 5

Ou

tpu

t p

ow

er (

kW)

Wind speed (m/s)

Investigated wind turbines' power curves comparison (Zoomed in view)

Enercon 330kW





67

V.i RE POTENTIAL IN CURRENT POWER SYSTEM

It was found that because of the sensitivity of the power system to be ranging somewhere

between 50 and 100 kW, the potential of RE in the current power system is zero. This is also

due to the size of the power system. It is known that the larger the engine used to produce

energy, the more efficient they are, hence, the harder it becomes for smaller RE power

systems to economically compete.

V.ii RE POTENTIAL AS A STANDALONE

As it was observed in the analysis section above, the most economically viable system most

of the time is a combination of several FWS 100 kW wind turbines and the selected diesel

generators. For a project starting in 2012, this system does not become more economically

viable than the selected diesel generators on their own, if the life of the project is less than 7

years. It was also noticed that the standalone situation is more economically feasible than the

current power system if the mine power system is located more than 4 kilometres away from

the village (Assuming: $250,000 per km for a 22 KV transmission line). Nevertheless, the

carbon emissions of the standalone power system when only the selected diesel low load

cycle generators from ENGEN Power are used is higher than the current power system. This

was explained due to the higher efficiency of larger generators (mine power system) and the

use of gas in the generation of electricity (87% gas, 13% diesel). In fact, the carbon content of

gas is less than the diesel carbon content (APPEA, 2011). Hence, even though the standalone

situation is more economically favourable than in the other systems, the carbon emissions

might be worse. The standalone configuration should not then be recommended if it leads to

more carbon emissions. It can be observed that, for projected values, RE power systems

become economically viable compared with the selected diesel generators, in 2014, 2016 and

2018 if the project life is 5, 4 and 3 years respectively. This shows high potential for RE

power systems in a standalone situation in the near future as long as the mine power system is

located more than 4 kilometres away from the village. It is also important to mention that the

standalone situation will also lead to some reduction in the energy loss through transmission

lines.


68

VI RE POWER SYSTEMS’ DRIVERS

Australia has great potential for the use of renewable energies and many different resources

yet to be harvested to their full potential (Kuwahata et al. 2010). Some of the drivers for

considering RE power systems were discussed in the literature review and aims of this report.

These are as followed:

- Climate change

- Abundance of RE resources (Figure 10 and 15)

- Environmental protection (Cleaner Air, low environmental impact and atmospheric

carbon reduction)

- Energy security (secure and stable supply and independent from other countries)

- Green Jobs creations

- Increasing cost of energy

- Raising community awareness

- Gaining a competitive advantage (Branding, ethical investment etc.)

- Tax advantage

- Embodied energy payback period

- Increasing regions‟ economic diversity

69

4 GEOTHERMAL AIR-CONDITIONING POTENTIAL IN MINING

VILLAGES

The major energy demand for MMG village can be observed in Figure 3 to be in January and

February where it is the hottest and AC is used the most. Hence, an alternative AC system

was investigated. In this case, it was chosen to assess the potential of geothermal heat pump

technology, using MMG village as a case study. More information on the current and

geothermal AC system is provided below.

4.1 CURRENT SYSTEM BACKGROUND

The current system at MMG village was investigated. The current AC system being used is a

reverse cycle air source heat pump system.

Air source heat pump systems (more commonly known as reverse-cycle AC) use outside air

as a heat source or sink. Hence, the heat pump transfers heat from outdoors to indoors or vice

versa, depending on the requirement. The heat pump consists of a refrigerant circulating to

transfer heat with the help of a condenser and a compressor (Sumner, 1976). Air source heat

pump systems are widely available in Australia. Their efficiency in converting electricity to

cooling or heating is very high. However, these systems are powered with electricity which

indirectly generates carbon dioxide emission as the MMG village power system is powered

using fossil fuels. The AC system at MMG village is composed of Fujitsu reverse cycle air

source heat pumps. The different size and number of AC unit installed in the village can be

observed in Table 24 below.

4 Geothermal Air Conditioning Potential in Mining Villages

70

Table 24: MMG village AC unit number and size (Based on cooling capacity)

AC per building

AC1 AC2 AC3

Building Building

Quantity

Unit

number

Capacity

(kW)

Unit

number

Capacity

(kW)

Unit

number

Capacity

(kW)

Donga 40 4 2.5 n/a n/a n/a n/a

Ice Room 1 1 5 n/a n/a n/a n/a

Exec and

disabled

accommodation

1 1 5 1 4 n/a n/a

Admin 1 6 5 1 2.5 n/a n/a

Gym 1 8 5 n/a n/a n/a n/a

WWTP and

WTP 1 1 3.5 n/a n/a n/a n/a

Kitchen 1 13 9.4 3 5 1 3.5

For this analysis, an approximation of the current AC system‟s cost was required. The

assumption made to estimate the current AC system cost is provided in Table 25.

Table 25: Current AC system installed cost estimation (SPLIT 4 YOU, 2011)

ASHP

Appliance Unit Cost per Unit ($) Cost

($)

2.5kW A Heat pump 160 1524 243840

3.5kW A Heat pump 2 1658 3316

4kW A Heat pump 1 1800 1800

5kW A Heat pump 18 2139 38502

6kW A Heat pump 14 2338 32732

Quantity discount 20%

Total ($) 256,152.00


71

4.2 GEOTHERMAL HEAT PUMP TECHNOLOGY

A geothermal or Ground Source Heat Pump (GSHP) uses the same concept as an air source

heat pump. Nevertheless, instead of using the outside air as a heat source of sink, these

systems use the ground. Hence, heat is transferred from a ground loop or ground water

indoors or vice versa. Geothermal systems are a rising technology within Australia, although

they have been in existence for many years and are well known especially in America and

Sweden. The efficiency of GSHPs is even higher than that of air source heat pumps. The

ground remains at lower temperatures in summer and higher temperatures in winter than air

and the efficiency of the heat pump is increased when the source or sink is at closer

temperatures to the desired room temperature. Hence, their lower energy use makes them

quite attractive for sustainable heating and cooling. These systems also use electricity, hence

indirectly emitting carbon dioxide. It is also important to mention that GSHPs can also

produce hot water for no extra operating cost. Hence, they can be connected to the hot water

system of the facility and save energy in this area too. Figure 50, is a schematic diagram for a

GSHP, starting from heat exchange from the ground, evaporation, then condensation and

further heat exchange (Glassley, 2010)

(http://heatexchanger-design.com/wp-content/uploads/2011/01/ground-source-heat-pump.jpg)

Figure 49: Ground source heat pump schematic diagram

http://heatexchanger-design.com/wp-content/uploads/2011/01/ground-source-heat-pump.jpg


72

Many different configurations of ground loop are available. The main ones are highlighted

below.

4.2.1 GROUND WATER SYSTEMS

For the use of groundwater systems sufficient groundwater, with suitable thermal energy, is

required to be available. Groundwater often has contaminants such as mineral salts that can

potentially affect equipment detrimentally. Hence, filtration may be required to deal with this

issue.

Figure 50: Groundwater system schematic (McQuay, 2002)

Open Loop:

Open loop groundwater systems draw energy directly from pumped groundwater. The

groundwater is directly supplied to the heat pump. This system is fairly liable to be affected

by groundwater quality (Caneta, 1995)

Closed Loop:

Closed loop groundwater system draw energy directly from pumped groundwater like the

open loop groundwater system discussed previously. However, this system uses an isolation

plate-frame heat exchanger between the drawn groundwater and the heat pump. This system

is less liable to be affected by groundwater quality (Caneta, 1995)


73

4.2.2 GROUND HEAT EXCHANGER SYSTEMS

Ground heat exchanger systems include horizontal and vertical loops. The ground

temperature at a certain depth remains fairly constant through the year. These systems take

advantage of this by using the ground as a heat source or sink. They are composed of a sealed

ground loop inside of which there is water or coolant which is not in contact with the

surrounding ground. In this case, only heat is transferred.

Horizontal loop:

Horizontal loops run horizontally along the ground, close to the surface. It takes advantage of

the change in soils temperature relatively rapidly close to the surface for heating or cooling

(Caneta, 1995).

These are quite easy to install, but require more surface area. They can have diverse

configurations.

Figure 51: Horizontal ground loop system (McQuay, 2002)

Vertical loop:

These run perpendicular to the surface. They can be several hundred metres deep. Similar

principles as other closed loop systems are used. At these depths, the temperature is fairly

constant through the year (Caneta, 1995).


74

These require less surface area than the horizontal loop, hence, they can be appropriate for

projects where surface area is limited. However, they are harder to install. They can also have

diverse configurations.

Figure 52: Vertical Ground loop system (McQuay, 2002)

4.2.3 SURFACE WATER HEAT EXCHANGER SYSTEM

Surface water heat exchanger systems use a nearby surface water body as a heat source or

sink as opposed to the ground. The surface water body can be a pond, lake or an ocean and

needs to be of a sufficient size to handle the required loads.

Closed loop systems run water or coolant in sealed pipes in the water body.

Open loop systems pump water out of the water body and draw energy from or release energy

into it as required (Caneta, 1995).


75

Figure 53: Surface water system (McQuay, 2002)

4.3 GSHP AT MMG VILLAGE

As mentioned previously, AC at MMG village is predicted to take a large part of the load.

During the site visit at MMG village, the different configurations that the GSHP could take

were investigated. There are many ways this system could be installed. However, due to

comfort reasons and space limitations, only two configurations were identified to be possible

for MMG village. These are illustrated in Figure 55 and 56 below. These configurations were

undertaken with the help of Colin Hayes and Steve Lucks. Figure 55 shows the water to

water heat pump configuration for a Donga. A water to water heat pump, is a heat pump that

transfers heat from water to water. In this situation, water fan coil units are required to

transfer heat or cool from the water to the air. This would be the most economic, but would

restrain temperature control in each room. In this situation, each room would have to be set at

similar temperature. Hence, it was decided to be inappropriate for Dongas. Figure 56

illustrates the water to air heat pump configuration for a Donga. A water to air heat pump, is a

heat pump that transfer heat from water to air to vice versa. This configuration was chosen to

be the most appropriate as in this case as each room would be able to be set at independent

temperatures. In the case where one large room requires to be set at the same temperature

(e.g. kitchen, gymnasium and recreational room), it was decided to use the configuration

illustrated in Figure 57. It is important to mention that each selected heat pump must be

reverse cycle. Figure 58 represents the heat and cool flow of the heating and cooling mode of

a GSHP system.


76

Figure 54: Water to water heat pump configuration for Dongas

Figure 55: Water to air heat pump configuration for Dongas

Figure 56: Water to water heat pump configuration for large rooms


77

Figure 57: Heat and cool flow of the heating and cooling mode of a GSHP system

4.4 GSHP SYSTEM SIZING

Most of the MMG village buildings require air-conditioning except for the laundries. Each

building has their external walls in contact with the outside environment. Some of these

buildings (e.g. Dongas and executive and disabled accommodation) have appropriate passive

solar orientation while others (ice room, gymnasium and recreational room) have poor

passive solar orientation and window locations. To be able to assess the potential of

geothermal AC at MMG village, rough sizing and cost estimation of the geothermal systems

were undertaken.

4.4.1 LOAD CALCULATION

Before sizing the geothermal system the heating and cooling load of the system must be

determined. It is known that MM is located in a cooling climate, where more energy is used

to cool than heat (YourHome, 2010). Hence, the load was calculated according to the peak

cooling load. In this situation, it was assumed that the current air-conditioning system was

sized appropriately. Hence, the cooling load was calculated depending on the cooling ability

of the current AC system. This can be observed in Table 26 below.


78

Table 26: Cooling load calculation

AC per building

AC1 AC2 AC3 Load

(kW) Building Building

Quantity

Qua

ntity

Capacit

y (kW)

Qua

ntity

Capacit

y (kW)

Qua

ntity

Capacit

y (kW)

Donga 40 4 2.5 n/a n/a n/a n/a 400

Ice Room 1 1 5 n/a n/a n/a n/a 5

Exec and disabled

accommodation 1 1 5 1 4 n/a n/a

9

Admin 1 6 5 1 2.5 n/a n/a 32.5

Gym 1 8 5 n/a n/a n/a n/a 40

WWTP and WTP 1 1 3.5 n/a n/a n/a n/a 3.5

Kitchen 1 13 9.4 3 5 1 3.5 140.7

MMG village cooling LOAD (kW) 630.7

The peak cooling load of MMG village was determine to be around 630kW.

4.4.2 SYSTEM SIZING AND COST ESTIMATIONS

For this study, a general ground loop was considered. However, firstly the different types and

sizes of heat pumps used (water to water or water to air) needed to be determined. The way

the different GSHPs would be distributed at MMG village are represented in Table 27.


79

Table 27: MMG village GSHP number and size (Cell coloured in yellow are water to water

heat pumps and uncoloured cell water to air heat pumps)

AC per building

AC1 AC2 AC3 AC4

Qua

ntity

Capacit

y (kW)

Qua

ntity

Capacit

y (kW)

Qua

ntity

Capacit

y (kW)

Qua

ntity

Capacit

y (kW)

Donga 40 4 2.5 n/a n/a n/a n/a n/a n/a

Ice Room 1 1 5 n/a n/a n/a n/a n/a n/a

Exec and disabled

accommodation 1 1 5 1 4 n/a n/a n/a n/a

Admin 1 2 5 1 2.5 1 20 n/a n/a

Gym 1 2 20 n/a n/a n/a n/a n/a n/a

WWTP and WTP 1 1 3.5 n/a n/a n/a n/a n/a n/a

Kitchen 1 1 65.8 1 56.4 3 5 1 3.5

The heat pump selection was based on the following criteria:

- Water to air heat pump

- Water to water heat pump

- Needs to meet the load

- Needs to be able to reverse cycle

- Readily available in Australia

- Maintainable locally

- Affordable

A variety of manufacturers were sourced to determine availability of the required heat pumps.

These are listed in the appendix section


80

Table 28 is a summary of those Australian manufactures and/or distributors that supplied the

different heat pumps and that had them available.

Table 28: Available size of GSHP in Australia

Water to water (kW) Water to air (kW)

Water furnace 7.034 to 52.755 2.638 to 87.925

Climate Master 6.341 to 26.9 4.39 to 17

McQuay 10.551 to 123.095 1.759 to 123.095

Trane 10.551 to unknown n/a

Once the availability of the necessary heat pumps was confirmed, the ground loop was sized.

As discussed previously, there are two main types of ground loop configurations, horizontal

and vertical. Table 29 provides guidelines on sizing and costing of vertical and horizontal

ground loops depending on the load.

Table 29: Horizontal and vertical ground loop sizing and costing guidelines (McQuay, 2002)

Ground loop

type Size Cost ($) Comment

Horizontal

2500ft2 per ton of load

(66.039m2 per kW)

Trenches: 150 to 220 ft per ton

(13 to 19.066m per kW)

600 to 800 $/ton

(170 to 227

$/kW)

Typical loop temperature

vary from 35F (1.67C) to

100F (37.78C)

Vertical

250ft2 per ton of load

(6.604 m2 per kW)

180 to 250 ft of borehole per

ton

(15.6 to 21.666m per kW)

900 to 1300 $/ton

(256 to 370

$/kW)

Vertical loop temperature

remain the same through the

year

Typical loop temperature

vary from 35F (37.78C) to

90F (32.22C)


81

In this case, a 1 to 1exchange rate between USD and AUD was used.

Horizontal loop sizing: 8190 to 12011.6 m trench

Horizontal loop cost: $107,100 to $143,010

Vertical loop sizing: 9828 to 13649.6 m borehole or 196 to 273, 50 m boreholes

Vertical loop cost: $161,280 to $233,100

As soil conductivity at MM would be lower than average due to very dry sandy soils, it was

decided to select a ground loop costing $300,000.

A trend cost of GSHPs depending on their size was found and used. However, the cost was

scaled down to match current pricings. The different assumed heat pump costs are available

in Table 30.

Table 30: MMG village GSHP cost estimation (Cummings, 2008)

GSHP

Appliance Unit Cost per Unit ($) Cost ($)

Thermal conductivity test 1 50000 50000

2.5kW A Heat pump 160 4214 674240

3.5kW G Heat pump 2 4499.6 8999.2

4kW G Heat pump 1 4642.4 4642.4

5kW G Heat pump 7 4928 34496

20kW G Heat pump 3 9212 27636

56kW G Heat pump 1 19493.6 19493.6

65kW G Heat pump 1 22064 22064

Ground Loop 1 300000 300000

Contingencies 1 110000 110000

Quantity discount 20%

Total ($) 1,001,256.96


82

4.4.3 POTENTIAL OF GSHP AT MMG VILLAGE ANALYSIS

I SUBSTITUTION OF THE ENTIRE CURRENT AC SYSTEM WITH A GSHP SYSTEM

POTENTIAL

The payback period of the geothermal system was undertaken using the NPC of the system.

The estimated electricity cost from the BEC engineering report was used for 2012 and 2013.

It was noticed that the electricity cost was predicted to increase from 2012 to 2013 by 6.4%.

To take a conservative approach, an annual inflation of 6% was selected for the electricity

cost from 2014 onward. A discount rate of 8% was assumed for the NPC calculation. The

NPC was calculated using the following formula:

NPC =

With:

Annual return = cost saved from using the geothermal system

Discount rate = 8%

Year no. = The number of years the return is occurring from January 2012

A payback period was obtained by comparing the use of the geothermal system instead of

using the current system.

Assumption made for the analysis:

- Average yearly COP of 5 for GSHP

- Average yearly COP of 2.7 for current system

- CAPEX of GSHP: $1,001,256.96

- CAPEX of current system: $256,152.00

- Annual cooling and heating energy required: 40% of overall load = 435,600 kWh

- Annual water heating load met by GSHP: 16% of overall load = 174,240 kWh


83

Table 31: Payback period estimation comparison with current system (NPV: Net Present

Value)

Year

No Year

Electricity

Cost

($/kWh)

Annual

return ($) NPC ($)

Accumulated

return ($) NPV ($)

0 2012 0.236 58652.88 58652.88 58652.88 -686452.08

1 2013 0.251 62430.43 57805.96 116458.83 -628646.13

2 2014 0.266 66176.26 56735.48 173194.31 -571910.65

3 2015 0.282 70146.84 55684.82 228879.13 -516225.83

... ... ... ... ... ... ...

12 2024 0.477 118511.60 47062.59 685857.41 -59247.55

13 2025 0.506 125622.30 46191.06 732048.47 -13056.49

14 2026 0.536 133159.64 45335.67 777384.14 32279.18

15 2027 0.568 141149.22 44496.12 821880.26 76775.30

Carbon emission avoided by using GSHP instead of the current system:

Carbon emission from Diesel (Values obtained from assumptions made in REMAX):

Energy saved (kWh) x 13% =

250,000kWh x 13% = 32,500kWh produced from Diesel

Energy produce from diesel (kWh) x Heat rate diesel (L/hWh) x Diesel carbon

content (t(CO2)/L) =

3 2500 x 0.26 x 0.002683 = 22.67 t(CO2)

Carbon emission from Gas (Values obtained from assumptions made in REMAX):


250,000kWh x 87% = 217,500kWh produced from Gas

x

x Gas carbon content (t(CO2)/m

3) =

x

x 0.00199 = 111.84 t(CO2)


84

Yearly saving using the GSHP instead of the current saving is around 250MWh and 135

tonnes of carbon dioxide emissions. The payback period in this case is 15 years.

A capital cost, annual water heating load and annual total heating and cooling load sensitivity

analysis was undertaken to observe the effects of changing these values on the payback

period. It can be observed in Figure 59 that for increasing capital cost, the payback period is

higher. In Figure 60 and 61, it can be seen that increase in water heating and total heating and

cooling load leads to lower payback period.

Figure 58: GSHP system capital cost sensitivity analysis (Capital cost: $1,001,256.96)

Figure 59: Annual heating and cooling load sensitivity analysis

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85

Figure 60: Annual water heating load sensitivity analysis

II SUBSTITUTION OF MAJOR AC DEMAND AREA WITH A GSHP SYSTEM ANALYSIS

As it was previously observed the GSHP system could lead to a shorter payback period when

use more appropriately. This and the following sections were undertaken to verify this.

In this situation, the potential of using a GSHP system instead of the current one was also

investigated. However, the GSHP is only looked at for a room with fairly constant and high

AC demand throughout the year. Hence, it was decided to choose the kitchen as a case study .

Table 27 shows that the peak cooling load in the kitchen is just above 100kW. Here, a 50kW

system was modelled.

Assumptions:



- CAPEX of GSHP (50kW system): $185,000.00 (Geothermal WA‟s quote via email)

- CAPEX of current system (50kW air source heat pump system): $30,000.00

- Annual cooling and heating energy required:

Maximum capacity (kW) of AC system x 80% x 20 hours per day x 365 days a year =

50 x 0.8 x 20 x 365 = 292,000kWh

- Annual water heating load met by GSHP:

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86

There are two hot water systems installed for the kitchen. As the AC system is rated for

about half of the load, it was estimated that the GSHP system would heat up only one of the

hot water systems. Hence,

Average daily energy use by hot water system (kWh) x 80% x 365 days =

25 (Figure 73) x 0.8 x 365 = 7,300kWh

The payback period in this situation was calculated the same way as the previous section and

using the same discount rate (8%).


AC system operating 20 hours a day

Year

No Year

Electricity

Cost ($/kWh)

Annual

return ($) NPC ($)

Accumulated

return ($) NPV ($)

1 2012 0.236 17948.12 16618.63 16618.63 -138381.37

2 2013 0.251 19104.07 16378.66 32997.29 -122002.71

... ... ... ... ... ... ...

9 2020 0.378 28725.46 14369.88 139462.65 -15537.35

10 2021 0.400 30448.99 14103.77 153566.43 -1433.57

11 2022 0.425 32275.93 13842.59 167409.02 12409.02

12 2023 0.450 34212.48 13586.25 180995.27 25995.27




76,028kWh x 13% = 9,883.64kWh produced from Diesel



9883.64 x 0.26 x 0.002683 = 6.9 t(CO2)


87



76,028kWh x 87% = 66,144.36kWh produced from Gas

x


3) =

x

x 0.00199 = 34.0 t(CO2)

Yearly saving using the GSHP instead of the current saving is around 76MWh and 70.9


A capital cost sensitivity analysis was undertaken to observe the effects of changing capital

cost on the payback period. In Figure 62 it can be seen that for increasing capital cost, the

payback period is higher


(Capital cost: $185,000)

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88

III SUBSTITUTION OF MINOR AC DEMAND AREA WITH A GSHP SYSTEM ANALYSIS

In this situation, the potential of using a GSHP system instead of the current system only in a

room where the AC demand is fairly low throughout the year was investigated. In this

situation the same system as assessed just previously (50kW) was investigated. However, in

this case, it was assumed that the system operated for 10 hours a day.

Assumptions:



- CAPEX of GSHP (50kW system): $185,000.00 (Geothermal WA‟s quote via email)

- CAPEX of current system (50kW air source heat pump system): $30,000.00

- Annual cooling and heating energy required:

Maximum capacity (kW) of AC system x 80% x 10 hours per day x 365 days a year =

50 x 0.8 x 20 x 365 = 146,000kWh

- Annual water heating load met by GSHP:

As mentioned previously two hot water system are available for the kitchen. As the AC

system is rated for about half of the load, it was estimated that it would heat up one of the hot

water system only. Hence,

Average daily energy use by hot water system (kWh) x 40% (As it only operates 10 hours a

day) x 365 days =

25 (Figure 73) x 0.4 x 365 = 3,650kWh

The payback period in this situation was calculated the same way as the previous section and

using the same discount rate (8%).


89


AC system operating 10hours a day

Year No Year

Electricity

Cost

($/kWh)

Annual

return ($) NPC ($)

Accumulated

return ($) NPV ($)

1 2012 0.236 12076.04 11181.52 11181.52 -143818.5

2 2013 0.251 12853.81 11020.07 22201.59 -132798.4

... ... ... ... ... ... ...

14 2025 0.505 25864.38 8805.815 139557 -15443.05

15 2026 0.535 27416.25 8642.744 148199.7 -6800.301

16 2027 0.568 29061.22 8482.694 156682.4 1682.3923

17 2028 0.602 30804.9 8325.607 165008 10007.999




51,154kWh x 13% = 6,650.02 kWh produced from Diesel



6650.02 x 0.26 x 0.002683 = 4.6 t(CO2)



51,154kWh x 87% = 44,504 kWh produced from Gas

x


3) =

x

x 0.00199 = 22.9 t(CO2)

Yearly saving using the GSHP instead of the current saving is around 51MWh and 27.5



90

As undertaken previously, a capital cost sensitivity analysis was undertaken to observe the

effects of changing capital cost on the payback period. In Figure 63 it can be seen that for

increasing capital cost, the payback period is higher


(Capital cost: $185,000)

IV ANALYSIS SUMMARY

In the case where the GSHP system is used to substitute the current air source heat pump

system, the payback period was found to be around 15 years. It was also observed that an

increase in the space heating and cooling or water heating load, leads to a lower payback

period and vice versa. Hence, two similarly sized systems with different heating and cooling

loads were investigated. A 50 kW GSHP system operating 10 and 20 hours a day over the

year was investigated. As it can be seen in Figure 64, the same fluctuation in capital cost lead

to higher change in payback periods when only operating 10 hours a day. This shows that a

geothermal system operating near its maximum capability is economically a safer decision to

make. It is also important to mention that the cost used for the 50 kW geothermal system

($185,000) was quoted by Geothermal WA. This system has a diagonal ground loop

configuration using copper pipes. Hence, it is estimated that the cost of a horizontal ground

loop configuration system using on-site available equipment to dig the trenches would be

much cheaper ($20,000 to $60,000 less). In this situation, for a 50kW system operating

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91

around 20 hours a day (e.g. kitchen), a payback period around 6 years could be observed.

This confirms that a geothermal system could have high potential in mine site village if sized

appropriately and used in high AC demand areas such as the kitchen.

It is also important to mention that using geothermal AC in a standalone power system

situation would lead to a smaller power system required due to a smaller load. Hence, capital

cost in the power system infrastructure as well as components would be reduced.

Figure 63: Capital cost sensitivity analysis comparison for the 50kW system operating 10 and

20 hours a day (Capital cost: $185,000)

y = 0.1161x + 16.571

y = 0.0714x + 10.571

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Operating 10 hours a day

Operating 20 hours a day

92

5 DAVID GOODFIELD’S PHD

Another aim of this project was to assist DG in undertaking some tasks associated with his

PhD. These are discussed below

5.1 PREPARATION OF MONITORING DEVICES FOR MMG VILLAGE

This task was completed between the 6th and 17th of June 2011, where a trial logging

system was set up and experimented. This task included the following steps:

Read specifications for the logger and each measurement device

Connection of different types of measuring devices to the data logger

Programming the data logger to collect information accordingly with

the HOBO software

Connection and familiarisation with the wireless transmitters and

receivers

Collection of data over one minute and longer period of times

Experimenting with the different data analysis tools provided by the

HOBO software

More information on the logger as well as the sensors being used for monitoring

purposes at MMG village are available in the appendix section of this report in Table

50. An illustration on how the monitoring system is going to be operating is also

provided in Figure 67.

5.2 INVESTIGATION OF DIFFERENT SOFTWARE FOR OPERATIONAL

AND EMBODIED ENERGY CALCULATION OF MMG VILLAGE

A list of the investigated software and comment is available in Table 34 below. This

software was investigated so DG could be assisted while undertaking operational and

embodied energy calculations of MMG village. This task is discussed further in its

own task section below.

5 David Goodfield’s PhD

93

Table 34: Investigated software and comments

Software Investigation’s Comments

SimaPro (Lifecycle

analysis tool)

To acquire a general understanding on how to use this software, the “Wooden

Shed” tutorial (Figure 158) was undertaken. The software manual as well as

help sections were also read. More tutorials were requested to the tool

designer but none was provided. This tool is designed to undertake wide range

of lifecycle assessments.

eTool (Lifecycle

analysis tool)

To acquire a general understanding on how to use this software, the online

available tutorial was undertaken. The software manual as well as help sections

were also read. More tutorials were requested to the tool designer but none was

provided. This tool is mainly developed to calculate buildings‟ and houses‟

embodied and operational energy.

Gabi (Lifecycle

analysis tool)

To acquire a general understanding on how to use this software, the “Steel

paper Clip” tutorial (Figure 159) was undertaken. The software manual as well

as help sections were also read. More tutorials were requested to the tool

designer but none was provided. This tool is designed to undertake wide range

of lifecycle assessments.

ICE(UK) (Lifecycle

analysis tool)

This software is mainly a database providing the embodied energy of different

materials depending on their concentrations. This tool outputs can be used as

inputs in Gabi, SimaPro or eTool.

BERS (Building

Energy Rating

Software)

This software is used to perform home energy ratings. The heating and cooling

load is calculated per month and the comfort zone setting cannot be changed.

This software wanted to be used to performed heating and cooling load

calculation for AC sizing but was not found ideal for this application.

HOMER (Energy

modelling software)

HOMER was previously used by the intern to undertake hybrid systems energy

modelling. Hence, no further investigation was required. However, previous

work undertaken using this software as well as articles about the use of this

software for energy modelling were investigated. This software was used to

undertake the potential of RE as a standalone system in mine site camp using

MMG village as a case study.

RETScreen (Pre-

feasibility

assessment tool)

RETScreen was previously used by the intern to undertake pre-feasibility

assessments. Hence, no further investigation was required. This software is

ideal to assess the feasibility of any RE power system and undertake sensitivity

analysis.


94

5.3 DIAGRAM MODIFICATION

DG requested assistance several times to help update the initial conceptual model for

the carbon neutral mine site village diagram that he previously created. The previous

and updated diagram can be observed in Figure 65 and 66 respectively.

Figure 64: Original conceptual model for carbon neutral mine site village (Goodfield, 2011)


95

Figure 65: Updated conceptual model for carbon neutral mine site village (Goodfield, 2011)

5.4 MMG VILLAGE MONITORING SYSTEM COMMISSIONING

5.4.1 MMG VILLAGE SITE VISIT AND MONITORING SYSTEM COMMISSIONING

The commissioning of the MMG village‟s monitoring system was done by Matricon‟s

electricians prior to the site visit. The configuration of the monitoring system can be seen in

Figure 67 below. More information on monitoring system is also available in the appendix

section 9.9. However, even though the commissioning was undertaken, some issues with two

of the main loggers were noticed and needed to be resolved. Two of the loggers (MDB3 and


96

MDB5) were not communicating with the receiver. Hence, no data could be transmitted. In

addition, it was noticed that each sensor‟s serial number needed to be recorded from the

logger itself so they could be identified from the online database (HoboLink). Only serial

numbers were appearing in HoboLink, instead of their corresponding names. The visit to

MMG village took place from the 18th

to the 20th

of November. The timeline of the different

tasks undertaken during this visit are highlighted below.

- 18th

of November 2011:

Arrival at MMG village 2PM. On the first day, the problem from both loggers were

investigated and identified. One logger (MDB3) was set to not transmit any data (Closed

relay), which was modified, and the other one (MDB5) had Ethernet configuration issues.

- 19th

of November 2011:

The energy audit was undertaken during that day. More information on the energy audit is

provided in this section of the project below.

A meeting with Wayne Brindley, the current mine power system operator and manager was

organised and essential information on MMG mine power system collected.

Also, the light intensity in different location of the village was measured and recorded during

the evening.

- 20th

of November 2011:

An appropriate location for ground temperature monitoring on site at the village was denied

by the village manager due to underground services. Hence it was decided to dig monitoring

bores outside of the village boundaries.

Three bore holes were dug at different depths and temperature loggers were set up in them to

record six month worth of data. This data will then be used to identify the ground temperature

at MM and assess the potential of geothermal air-conditioning. While digging the bore holes,

no limestone layer was encountered. Hence a horizontal configuration for a geothermal AC

system can be a favourable option in this situation.

For appropriate comparison of temperature, data from 1, 2 and 3 metres under the ground

surface was to be recorded. The setup of these data loggers can be seen in Figure 68 and their

location can be seen in the Figure 69.


97

Figure 66: MMG village‟s monitoring devices configuration

Figure 67: Side view of monitoring bores set up near MMG village


98

Figure 68: Monitoring bore location at MM

5.4.2 COMMISSIONING RESULTS

Below can be seen screen shots (Figure 70 and 71) of the online database access to the

monitoring devices installed at MMG village. It is observed that all loggers are now operating

as required. Five minute averaged data are recorded by the loggers and then transmitted to the

online database every 30 minutes. If the connection is disabled, the data would keep being

recorded in the loggers and transmitted at the next successful connection. Depending on the

number of sensors attached to the logger, it will be able to keep the data for at least several

days, which would be sufficient to identify and resolve the connection issue. If the connection

problem is not resolved before the loggers reach the maximum of data they can store, the

loggers would stop logging to avoid wrapping and data loss. The data can then be

downloaded from the online database and analysed accordingly. A sample of the analysis on

one of the kitchen hot water system can be seen in Figure 72 and 73.

Figure 69: Hobolink screen shot of online access of monitoring devices (HOBOlink, 2011)


99

Figure 70: Hobolink screen shot of Kitchen monitoring sensors readings (HOBOlink, 2011)

Figure 71: Sample of kitchen hot water system power use from live collected data (1)

0

0.5

1

1.5

2

2.5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

KWh/hr

Hour

Hourly power use of the kitchen hot water system 1 (21/10/11)


100

Figure 72: Sample of kitchen hot water system power use from live collected data (2)

5.5 MMG VILLAGE EMBODIED AND OPERATIONAL ENERGY

CALCULATIONS

The embodied energy calculation of two buildings (donga and kitchen) of MMG village was

undertaken using eTool. A screen shot of one of the models can be observed in Figure 74

below. As the required information to calculate embodied energy for other buildings at the

MMG village has been collected, this task will be fully completed very soon. The operational

energy calculations of the buildings at MMG village have not yet been performed, as the

conclusions from the energy audit report and collected data are awaited to undertake this task.

0

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25

30

35

21 22 23 24 25 26 27 28

KWh/day

Day

Daily power use of the kitchen hot water system 1 in October


101

Figure 73: eTool screen shot of one Donga embodied energy calculation model (eTool, 2011)

5.6 MMG VILLAGE ENERGY AUDIT

As it was previously mentioned in this report, the energy audit of the MMG village was

undertaken on the 19th

of November 2011. Only the energy audit of one donga was

undertaken as they are all alike. The executive and disabled accommodation was not

available for the energy audit and could not be undertaken. Nevertheless the appliances

present in this building are the same as the ones in the dongas. The energy audit will then be

performed from plans provided by the builder as with the audit of the dongas undertaken

previously. The detailed energy audit is available in Table 51 to 61 section 9.11.

102

6 RECOMMENDATIONS

The recommendations from this study and report are as follows:

6.1 RECOMMENDATIONS FOR THE FULL COMPLETION OF THIS

STUDY

- More modelling using REMAX should be undertaken. REMAX should be updated to

erase the current limitations of the software. Once done, modelling of the mine

current power system will be more accurate. Moreover, the sensitivity analysis can be

performed faster.

- REMAX investigation should be redone using real life data (Load profile)

- The investigation potential in the current power system should be undertaken using

more configurations of wind turbine and PV arrays. In addition, for the “Wind

turbine(s) + PV array + current power system” configuration and further configuration

with a wider variety of wind turbines should be investigated.

- The power curves from the different wind turbines investigated should be requested to

the manufacturer in table forms and not graph. Graphs make the reading of the power

curve inaccurate and difficult.

- Geothermal AC should be investigated with real life data, knowing how much energy

is used by AC and HW systems.

- The major geothermal AC system should be investigated individually under different

criteria to assess what differentiate each of them (Load, peak load, capital cost,

performance, operational cost, environmental impact).

- The environmental impact of building a GSHP should also be assessed and taken into

consideration. Digging many bores or kilometres of trenches would definitely have

considerable environmental impacts.

- Embodied energy of different geothermal and standard AC systems should be

investigated and compared. It is known that GSHP systems have lower operational

energy, but the embodied energy over a project life is unknown.

- It was predicted that around 1.22% (540MWh per year) of the energy produced is lost

through transmission lines. This account for about half of the energy usage of the

village per year. Energy transmission line savings by removing the line between the

village and the mine power system should be looked at to be included in the

standalone configuration assessment.

6 Recommendations

103

6.2 RECOMMENDATIONS FOR FUTURE INTEREST

- It would be of great interest to have some sort of graph showing the potential of

carbon offset through different technologies for different size of mining camp.

- Solar AC should also be investigated. General information about solar AC is available

online, however, accurate costing of different systems was found to be difficult to

acquire. Solar AC could have a great potential in Australia due to the good solar

resource.

104

7 CONCLUSION

7.1 POTENTIAL OF RE POWER SYSTEMS AS A CARBON EMISSION

OFFSET SOLUTION

The potential of RE power systems in the current power system as well as in a standalone

situation was investigated as a carbon emissions‟ solution for mine site village‟s

development, using MMG village as a case study. Firstly, the current power system and

energy demand of the village were investigated. It was found that as in most mining village in

Australia, the village and mine operation share the same power system. Due to delays in the

handover of the village an annual load profile and predicted energy demand values could only

be applied in this project. The predicted power demand used was around 120 kW on average

with annual consumption of 1.1 GWh. The different RE‟s resources available at MM were

then determined (wind, solar radiation and biomass) and the appropriate technology available

to harvest these were selected using an MCA. It was found that PV and horizontal axis wind

turbine technology were the most appropriate systems for this project. In order to assess the

potential of RE as a carbon offset solution in the current power system, software was

specially developed. This software was referred to as REMAX. This was undertaken due to

limitations (e.g. cannot model mine site power systems) of using HOMER for this purpose.

However, HOMER was used to assess the potential of RE in standalone power systems. Due

to sensitivity issues (50 to 100 kW) of the current power system and the small ratio of the

village within the load (2.46%), research shows that the potential of RE in current power

system would be very low or zero. In the standalone situation, major capital cost savings

were identified if the transmission line between the mine power system and the village was

removed (≈$250,000 per kilometre). Some saving was also noted due to less energy loss in

transmissions‟ lines. Hence, it was found that, if the village is located more than 4 km away

from the mine‟s power system, the standalone configuration is more economically viable than

the current power system. Findings also show that a wind diesel hybrid power system is more

economically viable than the diesel, only if the project life is more than 7, 5, 4 and 3 years for

a project starting in January 2012, 2014, 2016 and 2018 respectively. Nevertheless, in the

case where the standalone system only includes diesel generators, the carbon emission was

determined to be higher, hence, not suitable as a carbon emission solution.

7 Conclusion

105

7.2 POTENTIAL OF GSHP SYSTEMS AS A CARBON EMISSION

OFFSET SOLUTION

The potential of GSHP technology as an alternative way to heat and cool mine‟s villages was

also assessed as a carbon emission solution, using MMG village as a case study. First, the

current system use was investigated and the cooling and heating load determined. Currently,

traditional reverse cycle AC units (air source heat pumps) are being used and the cooling load

was established to be around 630 kW. Substituting the entire current system with a GSHP

system led to payback periods around 15 years or more. However it was observed that when

the system was used near its full capacity (at least 20hours a day), payback period around 6

years or less were possible. Hence, it was conclude that GSHP systems could have high

potential in mine site‟s village if sized appropriately and used in rooms with high AC demand

such as the kitchen.

7.3 RECOMMENDATIONS

Although REMAX requires refining, it was found to provide a very useful tool to assess RE

power system potential in current mine power systems. In addition, this study needs to be re-

analysed using real life load profile that will be available when data has been collected for

long enough to represent the seasonal load variations. It is also recommended that more

sensitivity analysis of the different systems‟ configurations should be investigated. More

investigation on the mine power system should also be undertaken so the actual sensitivity of

the power system can be identified.

.

106

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110

9 APPENDIX

9.1 CASE STUDIES

9.1.1 MOUNT CATTLIN

The Galaxy Lithium mine at Mount Cattlin was investigated due to the RE power system

installed. The information about this site was gathered via email correspondences and an

organised meeting with James Rhee the designer of Mt Cattlin RE power system. More

information about this person can be found in the contact list in the appendix section of this

report. This power system was designed to power offices and has a battery backup system to

overcome power shortage. This mine is not connected to the grid and operates as standalone.

Other information is included in the following:

Capital cost: included into the AU$79 million construction budget

Estimated payback period: 7 years

Number of solar tracker installed: 14

Size of the PV array: 93kW

Number of wind turbines installed: 2

Size of each wind turbine: 3kW

Estimated energy produced by RE per annum: 226MWh which is about 1/6 of their daily

power use

Future plans:

Galaxy is looking to upgrade the system so that 100% of their power is supplied by

renewable power. It is planned to do this through an investor who would pay for the system

and Galaxy would then pay them for the energy. They are looking at building a 14MW wind

farm and 1 to 2MW solar farm around Galaxy area, which will support the local community

as well as the mine site.

Motivations of the project:

- The Managing Director and Board wanted to demonstrate that an environmentally

sensitive approach to mining activities is achievable and can be done

- Protect themselves against financial repercussions of the uncertainty of diesel pricing

and the soon to be introduced carbon tax

9 Appendix

111

- They prefer to do a sustainable mine and advertise their green approach for long term

economic and environmental benefits.

9.1.2 MOUNT ISA MINES

Xtrata Parkside installed a 155kW of solar PV array to supply power to the accommodation

complex. The main findings on this case study are available below (Xstrata, 2011).

- Type of system: Grid connected

- Installation cost: nearly $950,000.00

Motivation of the project:

- To demonstrate the effectiveness of solar technology to communities in North West

Queensland

9.1.3 NICKEL MINES “X” AND “Y”

Due to confidentiality reasons, the source as well as the name and specific location of these

two mines cannot be provided. These mines‟ information will be used to compare the impact

of the village energy consumption with the entire operation as well as for creating the generic

output information on carbon emission.

- “X”

o Type: Nickel mine

o Location: Pilbara

o Total energy use per year: 47 GWh

o Village and workshop energy use per year: 2.74 GWh

o Lifetime left: less than 2 years

o Power generation system: 9 x 1MW (gas) + 3 x 1MW(diesel, recently added)

9 Appendix

112

Figure 74: Energy use repartition at “X” mine per year

- “Y”

o Type: Nickel mine

o Location: Pilbara

o Total energy use per year: 17.8 GWh

o Village energy use per year: 1.35 GWh

o Lifetime left: around 18 month

o Power generation system: 8 x 1MW (Diesel), under normal operation 6 x

1MW

Figure 75: Energy use repartition at “Y” mine per year

94%

6%

Energy use repartition at "X" Mine per year

Total

Village + Workshop

92%

8% Energy use repartition at "Y"

Mine per year

Total

Village + Workshop

9 Appendix

113

9.2 SOLAR RESOURCE INVESTIGATION

Figure 76: Mount Magnet best, worst and average mean monthly global solar exposure over

1990 to 2010 (BOM, 2011)

9.3 WIND RESOURCE INVESTIGATION

9.3.1 BOM DATA

Table 35: Weibull distribution factor graph calculation

Bin Frequency Probability Cumulative

probability X = 1-(cumulative prob) ln(-ln(X)) ln(Vx)

0.5 936 2.21% 2.21% 97.79% -3.8012 -

0.6931

1.5 1784 4.21% 6.42% 93.58% -2.7126 0.4055

2.5 6856 16.19% 22.61% 77.39% -1.3615 0.9163

3.5 4888 11.54% 34.15% 65.85% -0.8729 1.2528

4.5 7982 18.84% 52.99% 47.01% -0.2813 1.5041

5.5 6785 16.02% 69.01% 30.99% 0.1582 1.7047

6.5 5638 13.31% 82.32% 17.68% 0.5496 1.8718

7.5 3745 8.84% 91.16% 8.84% 0.8860 2.0149

8.5 2168 5.12% 96.27% 3.73% 1.1909 2.1401

9.5 993 2.34% 98.62% 1.38% 1.4545 2.2513

10.5 358 0.85% 99.46% 0.54% 1.6542 2.3514

0 1 2 3 4 5 6 7 8 9

10

kWh/m2

Month

Worst, best and average year global solar radation per month from 1990 to 2010

Worst Year

Average

Best Year

9 Appendix

114

11.5 131 0.31% 99.77% 0.23% 1.8066 2.4423

12.5 51 0.12% 99.89% 0.11% 1.9239 2.5257

13.5 23 0.05% 99.95% 0.05% 2.0233 2.6027

14.5 16 0.04% 99.99% 0.01% 2.1818 2.6741

15.5 4 0.01% 100.00% 0.00% 2.2987 2.7408

16< 2 0.00% 100.00% 0.00% N/A N/A

9.3.2 NASA DATA

The NASA SSE data which was used below to investigate the wind resource consists of 22

years global average on a 1 by 1 degree grid (around 100 by 100km)


Magnet (NASA, 2011)

Month Wind speed

m/s

January 4.5

February 4.5

March 4.4

April 4.3

May 4.1

June 4.1

July 4

August 4

9 Appendix

115

September 4

October 4.2

November 4.7

December 4.6

Average 4.3


Mount Magnet (NASA, 2011)

3.9 4

4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8

0 2 4 6 8 10 12

m/s

Month

Monthly average wind speed at Mount Magnet

Wind speed

Average

9 Appendix

116

Figure 78: Long term daily diurnal variation in the monthly average hourly wind speed

for each month of the year at 50m above ground surface at Mount Magnet (NASA, 2011)

Figure 79: Annual average wind rose at 50m above ground level at Mount Magnet (NASA,

2011)

0

1

2

3

4

5

6

7

8

0:00:00 4:48:00 9:36:00 14:24:00 19:12:00 0:00:00

m/s

Time (hrs)

Long Term Monthly Averaged Hourly Wind Speed

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

1 5 9 13 17 21 25

29 33

37 41

45 49

53 57

61 65

69 73

77

81

85

89

93

97

101

105

109 113

117 121

125 129

133 137

141 145

149 153

157 161 165 169 173 177 181

185 189 193 197 201 205 209

213 217

221 225

229 233

237 241

245 249

253

257

261

265

269

273

277

281

285

289 293

297 301

305 309

313 317

321 325

329 333

337 341 345 349 353 357

9 Appendix

117


(NASA, 2011)


Magnet (NASA, 2011)

Determination of k and c:

To obtain the shape and scale factor for Mount Magnet wind resource the following was

undertaken:

9.00%

60.00%

30.00%

1.00% 0.00% 0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

1 4.5 8.5 12.5 16.8

Freq

uen

cy o

f o

ccu

ren

ce (

%)

Wind speed at Midpoint of Bin (m/s)

Frequency Histogram of Wind Speeds

0

20

40

60

80

100

120

0 5 10 15 20 25

Cu

mu

lati

ve p

rob

abili

ty (

%)

Wind speed (m/s)

Cumulative probability function

9 Appendix

118

- (1-cumulative probability) was obtained for each bins

- Ln(-ln(1-cumulative probability)) was then calculated for each bins

- Ln(vx) was acquired for each bins

- Ln(-ln(1-cumulative probability)) versus ln(Vx) was plotted

- A linear trend line was then fitted


surface

Table 37: Weibull distribution factor graph calculation

Bin

(m/s)

Probability

(%)

Cumulative probability

(%)

X = 1-(cumulative

prob) (%) ln(-ln(X)) ln(Vx)

1 9 9 91 -2.3611608 0

4.5 60 69 31 0.15801433 1.5040774

8.5 30 99 1 1.52717963 2.14006616

12.5 1 100 0 n/a 2.52572864

16.8 0 100 0 n/a 2.82137889

The straight line observed in Figure 82 is of the form y = a + bx

Where:

y = 1.7913x - 2.4013

-3

-2

-1

0

1

2

0 0.5 1 1.5 2 2.5

ln(-

ln(1

-cu

mu

lati

ve p

rob

abili

ty))

Ln(Vx)

Weibull distribution factor estimation graph

9 Appendix

119

- y = ln(-ln(1-cumulative probability))

- x = ln(Vx)

- a = -kln(c)

- b = k

Here y = a + bx is given as y = -2.4013 + 1.7913x, hence k = 1.7913 and c =

= 3.82

In this situation k = 1.7913 and c = 3.82 m/s

% winds < 3m/s = 45%

% winds > 6m/s = 100% - %winds < 6m/s

= 100% - 80%

= 20%

Figure 83: Load and wind resource seasonal variation comparison over the year (NASA,

2011)

0

1000

2000

3000

4000

5000

0 2 4 6 8 10 12 14

kWh/(d)

Month

Load and wind resource seasonal variation comparison over the year

LOAD

Wind Resource

9 Appendix

120

Figure 84: BOM purchased wind data annual average wind speed at MM (BOM, 2011)

4.1

4.15

4.2

4.25

4.3

4.35

4.4

4.45

4.5

4.55

4.6

2006 2007 2008 2009 2010

(m/s)

Year

Annual average wind speed at MM

9 Appendix

121

9.4 CURRENT POWER SYSTEM COSTING

Table 38: Current Power System Predicted Cost for 2012

Fixed

charge ($)

Deutz fixed

charge ($)

Variable

tariff ($)

Energy

use

(MWh)

Diesel

ratio

Gas

ratio

Diesel

cost

($/L)

Diesel

use (L)

Diesel

cost ($) Gas cost ($) overall cost ($)

jan 2952 3075 2015 130 0.13 0.87 1.1092 4394 4873.82 13289.25 26205.07

feb 2952 3075 2015 130 0.13 0.87 1.128 4394 4956.43 13289.25 26287.68

mar 2952 3075 1782.5 115 0.13 0.87 1.1468 3887 4457.61 11755.88 24022.99

apr 2952 3075 1317.5 85 0.13 0.87 1.1656 2873 3348.77 8689.13 19382.39

may 2952 3075 1085 70 0.13 0.87 1.1844 2366 2802.29 7155.75 17070.04

jun 2952 3075 1085 70 0.13 0.87 1.2032 2366 2846.77 7155.75 17114.52

jul 2952 3075 1193.5 77 0.13 0.87 1.222 2602.6 3180.38 7871.33 18272.20

aug 2952 3075 1116 72 0.13 0.87 1.2408 2433.6 3019.61 7360.20 17522.81

sep 2952 3075 1007.5 65 0.13 0.87 1.2596 2197 2767.34 6644.63 16446.47

oct 2952 3075 1116 72 0.13 0.87 1.2784 2433.6 3111.11 7360.20 17614.31

nov 2952 3075 1503.5 97 0.13 0.87 1.2972 3278.6 4253.00 9915.83 21699.32

dec 2952 3075 1643 106 0.13 0.87 1.316 3582.8 4714.96 10835.85 23220.81

Total 35424 36900 16879.5 1089 n/a n/a n/a 36808.2

0

44332.1

1 111323.03 244858.63

9 Appendix

122

9.5 MULTI-CRITERIA ANALYSIS

9.5.1 MCA CRITERIA WEIGHTING

The selected criteria and stakeholders were then used to obtain appropriate weightings for

each criterion. A rating from 0 to 10 according to the importance of each criteria depending

on the stakeholders was performed with 0 and 10 being of lowest and highest importance

respectively.

Table 39: Criteria weighting

Criteria

Stakeholders

Total

weighting Ranking

MM

resident

MMG

village

employee

MMG

village

shift

workers

Head

Office

Social

Education on use 0 9 6 8 6.9261% 2

Health and safety 6 9 6 6 6.2527% 6

Employment 8 8 2 5 5.0599% 10

Social

acceptability 8 7 8 2 4.1197% 15

Social benefits 8 5 5 2 3.3334% 18

Environmental

Materials use 5 6 5 4 4.4000% 13

Energy use 0 2 2 6 4.0410% 16

Biodiversity 8 5 5 5 5.0380% 11

Emissions 8 8 8 10 8.8268% 1

Compliance 6 6 5 8 6.7499% 4

Land use 2 2 2 3 2.4908% 19

Aesthetic 9 7 5 3 4.3021% 14

Economic

Capital cost 0 4 2 10 6.6370% 5

Operating cost 0 4 3 10 6.7913% 3

Economic

impacts of

organisation

through

stakeholders

6 8 6 5 5.5229% 8

9 Appendix

123

Technical

Efficiency 0 2 2 8 5.1774% 9

Reliability

(Continuity and

predictability of

performance)

0 8 2 4 3.8745% 17

Maturity 2 8 2 5 4.5970% 12

Implementation

duration 5 8 5 6 5.8596% 7

Scaling Factor 1 3 2 10 16

Total 81 116 81 110 100%

9.5.2 MCA OUTCOME

A rating following the guideline in Table 40 below was used to rate each criteria depending

on the option. This rating was then multiplied by the criteria weighting and a final rating was

obtained. More in depth explanation on the method used will be available in the final report

of this project.

Table 40: Rating guideline

Rating Meaning

1 Very Poor

2 Poor

3 Average

4 Good

5 Very Good

9 Appendix

124

Table 41: MCA final outcome (Afgan N and Carvalho M, 2002)

Field Criteria Weighting

WIND PV Solar Thermal Biomass Concentrated PV

Rating Final

Rating Rating

Final

Rating Rating

Final

Rating Rating

Final

Rating Rating Final Rating

Social

Education on

use 0.073244 3 0.219732 4 0.292976 2 0.146488 3 0.219732 3 0.219732

Health and

safety 0.066339 4 0.265357 5 0.331696 4 0.265357 3 0.199018 4 0.265357

Employment 0.053651 3 0.160952 2 0.107302 4 0.214603 4 0.214603 3 0.160952

Social

acceptability 0.044058 4 0.17623 5 0.220288 4 0.17623 5 0.220288 4 0.17623

Social benefits 0.035585 2 0.071171 3 0.106756 2 0.071171 1 0.035585 2 0.071171

Environmental

Materials use 0.046726 4 0.186905 3 0.140179 4 0.186905 4 0.186905 3.5 0.163542

Energy use 0.04252 5 0.212599 5 0.212599 4 0.170079 3 0.12756 4 0.170079

Biodiversity 0.053442 4 0.21377 4 0.21377 4 0.21377 3 0.160327 4 0.21377

Emissions 0.093413 5 0.467063 3 0.280238 3 0.280238 1 0.093413 2 0.186825

Compliance 0.071369 4 0.285476 4 0.285476 2 0.142738 5 0.356845 3 0.214107

Land use 0.026329 3 0.078988 3 0.078988 4 0.105317 5 0.131647 4 0.105317

Aesthetic 0.045843 3 0.13753 3 0.13753 2 0.091687 2 0.091687 3 0.13753

Economic Capital cost 0.069802 4 0.279206 3 0.209405 4 0.279206 5 0.349008 3 0.209405

Operating cost 0.071468 4 0.285873 5 0.357341 3 0.214405 2 0.142937 4 0.285873

9 Appendix

125

Technical

Efficiency 0.054425 4 0.217698 3 0.163274 3 0.163274 2 0.108849 4 0.217698

Reliability 0.041032 3 0.123095 3 0.123095 3 0.123095 5 0.205159 3 0.123095

Maturity 0.048651 5 0.243254 5 0.243254 4 0.194603 5 0.243254 3 0.145952

Implementation

duration 0.062103 3 0.18631 5 0.310516 3 0.18631 2 0.124206 3 0.18631

TOTAL 3.811210317 3.81468254 3.22547619 3.211021825 3.252946429

Ranking 2 1 4 5 3

9 Appendix

126

9.6 PROJECT’S CONTACTS

Table 42: Project‟s contact

Name Company,

occupation

Help Contact

Adam

McHugh

Lecturer, Energy

Studies at

Murdoch

university

Help using GaBi

lifecycle analysis

software

E: [email protected]

Antony

Piccinini

Head of

Renewable energy

group of

EcoNomics

WorleyParsons

Advice with

renewable energy

power system design

M: 0400 345 455

E:

Antony.Piccinini@WorleyParsons.

com

Brett Rice Director of Green

Energy Systems

(GES)

Information about

Amorphous solar

module and inverter

they use in their

systems

M: 0411 371 777

E:

[email protected]

Britton

Rife

Sales and

Customer Service

Bergey

Windpower

service

Cost estimation and

information for

Bergey 10kW wind

turbine


Bruce Solar West Cost estimations for

WestWind wind

turbines in Australia

P: 08 97 563 076


Bruce

Clare

Lead electrical

Engineer at BEC

engineering PTY

LTD

Mine site power

system

understanding

M: 0437 906 910


Bruce

Kingston

Manager QSE and

Office Services

Matricon

Mount Magnet gold

village monitoring

devices information

M: 0407 388 715

E:

[email protected]

David

Goodfield

PhD candidate at

Murdoch

university

Academic supervisor E: [email protected]

Dougal

Gillman

Account

Coordinator at

Apollo Energy

Costing on PV

modules, Inverters

and Small wind

turbine

P: 03 96 971 987


Chem

Nayar

Chairman and

Managing

Director of

REGEN Power

Low load cycle

generator technology

and PV modules,

inverters and Wind

turbines costs

M: 0401 103 451


Colin

Hayes

Director

Geothermal

Heating and

Cooling Australia

Shallow geothermal

system designer

E1:

colin.hayes@environmentalplumbi

ng.com.au

E2:

mailto:[email protected]













9 Appendix

127

[email protected]

M: 0405563197

James

Rhee

Swan Energy Mount Cattlin hybrid

power system

designer

M: 0400 317 811


Jim

Thomson

Outback Energy

Supply: Small and

medium size wind

turbine distributor

in Australia

Information about

small and medium

size wind turbine


Jonathan

Whale

Senior Lecturer,

Energy Studies at

Murdoch

University

General information

about Wind Turbines


Mark

McHenry

Engineering and

energy Murdoch

University

Assisting with

developing RE

power system for

MMG village


Martin

Anda

Chair of

Environmental

Engineering at

Murdoch

University

Academic supervisor E: [email protected]

Michael

Mazengrab

Assistant Manager

at the Office of

the Renewable

Energy Regulator

Assisting with

Renewable Energy

Certificates

information


Pat

Richards

Paul Hardisty

Assistant

To contact Paul

Hardisty

E:

[email protected]

Paul

Hardisty

Global Director of

EcoNomics

WorleyParsons

Business supervisor E:

[email protected]

m

Paul

Wilkinson

Matricon General and specific

information about

Mount Magnet gold

village

E:

[email protected]

Richard

Haynes

eTool Help with the eTool

software use and

problems

M: 0411 141 246


Richard

Johnston

Director of The

Windturbine

Company

Costing and

information about

the Endurance 5 and

50kW, Aircon

10kW, Evoco 10kW

and Gaia 11kW wind

turbines

M: 0417 316 642


Robert

Mailler

Director of

Engineering of

YellowDot

Energy,

Information about

Amorphous thin film

technology, PV

mounting, SMA

M: 0437 280 267
















9 Appendix

128

Renewable power

Systems

inverters and

batteries

Steve

Lucks

Solar engineering

Services

Any type of air

conditioning

specialist

M: 0412 766 477


Trevor

Pryor

Academic Chair,

Senior lecturer

Energy Studies at

Murdoch

University

Assisting in the use

of HOMER and

advice on the

process to design RE

power systems


Wayne

Brindley

Maintenance

Manager at MMG

mine (Ramelius

Resources)

Provide information

on the current and

future mine Power

system

M: 0448 888 610

E:

waynebrindley@rameliusresources

.com.au

9.7 COSTS

Table 43: Wind turbines costs (Better Generation, 2009 and emails from contacts)

Size

(kW)

Lifetime

(y)

Hub

height

(m)

Capital Cost ($)

excluding VAT Comment

Westwind

10kW 10 20 15

52k fully installed

excluyding groudn

work

Westwind

20kW 20 20 15

89.5k fully installed

excluding ground

work

Enercon

330kW 330 20 37 1100000 installed

Enercon

600kW 600 20 40 2550000 (per unit)

Aerostar6

10kW 10

24950 excluding

tower and installation 240V output no need of an inverter

Gaia Wind

11kW 11

65500 installed

excluding ground

work

400V output

Proven 6kW 6

28k to 36k fully

installed grid 240V





9 Appendix

129

connected

ProvenWT2500

3.21kW 3.21

16400 grid connected

installed no ground

work included

240V

Quiet

Revolution

QR5 6.33kW

6.33 25

45-52K fully installed unknown voltage

Samrey Merlin

GT 2.714

6.6K-8K including

everything and

depending on

anchored or stand

alone

Scirocco 6kW 6

30k-40k fully installed

depending on tower

size and site

48V

Skystream 3.7 2.4

12k to 15k fully

installed, generator

cost 5400

240V

Turby VAWT 2.5

installation 2000,

mast from 5 to 9m

1500 to 5k,

foundation 1k to 2.6k,

accessories up to 1.3k

240V

Ampair 6kW 6

20.7K just unit I think 240V

Bergey 10

18 to

43

25770 to 31770 for

the turbine and

installation 10150 to

17200

Price include a grid-synchronous

inverter and installation depends on

the tower height

Four Wind

Seasons

WindPower

10

44222 (16m tower) to

66146.50 (30M

tower) no installation

Source is ebay

Four Wind

Seasons

WindPower

20

66338 (18 ot 24m

tower) to 90751.60

(36.5m tower) no

9 Appendix

130

installation

Four Wind

Seasons

WindPower

50

around 155478.22 no

installation

Four Wind

Seasons

WindPower

100

around 293497.37 no

installation

Endurance

E3120 5.2

50k to 70k

Email: Price vary depending site

conditions, location, tower height and

type and connection type, price based

on single unit shipping, grid connected

in non remote location

Endurance

s343 55

380k to 500k






Gaia Wind

11kW 11

120k to 170k






Aircon 10kW 10

130k to 170k






Evoco 10kW 10

100k to 150k






Windspot

7.5kW 7.5

14

6 x 7.5kW units with

14m hydraulic towers Jim email

9 Appendix

131

= aorund $160k, $5k

per foundation need

to be allowed

Gilong 10kW 10

15

$43.7k + GST, allow

5k for installation

plus cabling

Jim email: 4sets per container, supply

only of 10kW turbine with 15m tower

with inverter 43.7k + gst

Table 44: PV modules costs including GST (Apollo Energy, 2011)

Manufacturer Rating

(W)

Quantity

(Unit)

Cost

($AUD)

REC Solar

235

1 to 39 674

40 to 199 616

200 to 559 539

560+ 506

190 1 423.69

235 1 524.04

Sanyo

210 1 to 39 968

40+ 880

235 1 to 39 1,210.00

40+ 1,100.00

Sharp 130 1 to 9 605

10+ 550

Solarfun

195 1 to 39 600.6

40+ 548.9

190

1 to 27 528

28 to 279 506

280 to 671 462

672+ 451

180 1 564.57

Suntech 190 1 to 25 528

26 to 51 511.5

9 Appendix

132

52 to 727 440

728+ 412.5

140 1 605

85 1 to 9 385

10+ 363

Amorphous

360W 1 to 28 232

29+ 200

550W 1 to 18 361.11

19+ 315.8

Table 45: Inverter cost (Apollo Energy, 2011)

Manufacturer Size

(kW)

Quantity

(unit)

Cost

($AUD) Comment

Aurora

Powerone

2 1 1,949.99 Included GST, Outdoor grid

connected

3.6 1 2,849.99 Included GST, Outdoor grid

connected

Fronius

1.5 1 1,419.00

2 1 2,200.00

2.65 1 2,200.00

3.5 1 3,520.00

4.1 1 2,530.00

4 1 3,610.14

5 1 2,805.00

8 1 6,320.00 Single or 2-phase

10 1 8,963.90 Three phase

12 1 9,117.80 Three phase

Ltronics 0.6 1 1,044.80 48V

9 Appendix

133

1.2 1 1,340.31 48V

1.8 1 2,100.30 48V

2.5 1 2,793.30 48V

3 1 3,091.80 24V

3.5 1 3,372.85 48V

4 1 4,158.00 24V

5 1 4,840.30 48V

7 1 5,810.50 48V

Outback

Power

Systems

2.6 1 3,190.00 12V

3 1 3,190.00 24V

3 1 3,300.00 48V

SMA

1.2 1 to 4 1,502.92 Sunny Boy

1.2 5 to 9 1,465.35 Sunny Boy

1.2 10+ 1,427.77 Sunny Boy

1.7 1 to 3 1,785.13 Sunny Boy

1.7 4 to 11 1,740.50 Sunny Boy

1.7 12+ 1,695.88 Sunny Boy

2 1 to 3 2,200.00 Sunny Boy

2 4 to 11 2,090.00 Sunny Boy

2 12+ 1,870.00 Sunny Boy

2.5 1 to 3 2,420.00 HF Sunny Boy

2.5 4 to 11 2,310.00 HF Sunny Boy

2.5 12+ 2,200.00 HF Sunny Boy

3 1 to 3 2,420.00 HF Sunny Boy, transformer

3 4 to 11 2,200.00 HF Sunny Boy, transformer

3 12+ 2,090.00 HF Sunny Boy, transformer

3 1 to 4 2,750.00 TL Sunny Boy, transformeless


3 10+ 2,420.00 TL Sunny Boy, transformeless





9 Appendix

134



5 1 to 3 3,630.00 Sunny Boy, Transformer

5 4 to 11 3,410.00 Sunny Boy, Transformer

5 12+ 3,410.00 Sunny Boy, Transformer

6 1 to 4 3,630.00 Sunny Mini Central, Transformer

6 5 to 9 3,520.00 Sunny Mini Central, Transformer

6 10+ 3,410.00 Sunny Mini Central, Transformer

7 1 to 4 4,369.14 Sunny Mini Central,

Transformerless


Transformerless

7 10+ 4,150.68 Sunny Mini Central,

Transformerless


Transformerless


Transformerless


Transformerless


Transformerless


Transformerless


Transformerless

10 1 to 3 5,720.00 Sunny Tripower, Transformerless,

3 phase


3 phase

10 12+ 5,280.00 Sunny Tripower, Transformerless,

3 phase

11 1 4,180.00 Sunny Mini Central,

Transformerless

9 Appendix

135


3 phase


3 phase


3 phase


3 phase


3 phase


3 phase

2 1 to 4 4,340.41 Sunny Island, Inverter Charger


2 10+ 4,123.39 Sunny Island, Inverter Charger

2.2 1 to 4 3,370.07 Sunny Island, Inverter Charger

2.2 5 to 9 3,285.82 Sunny Island, Inverter Charger

2.2 10+ 3,201.57 Sunny Island, Inverter Charger



5 10+ 5,304.18 Sunny Island, Inverter Charger

Victron

Energy

1.2 1 1,773.81

1.6 1 1,569.56

2 1 1,830.13 12V

2 1 1,773.81 24V

3 1 2,882.83

5 1 4,655.89

9 Appendix

136

9.8 SOFTWARE INPUT INFORMATION

9.8.1 WIND TURBINE INPUT INFORMATION

Table 46: Wind turbines input information

Wind Turbine Inputs

Name Unit Skystream Evance Gilong Gaia WW FWS FWS FWS Enercon Enercon

Capacity kW 2.4 5 10 11 20 50 100 200 330 600

Capital cost for 1, including

everything $/WT 23980 37965 56000 65000 100000 205000 390000 740000 1153000 1890000

Replacement of 1 turbine $/WT 19184 30372 44800 52000 80000 164000 312000 592000 922400 1512000

O and M cost per turbine $/(yr.WT) 1199 1898.25 2800 3250 5000 10250 19500 37000 57650 94500

Life time yrs 20 20 20 20 20 20 20 20 20 20

Hub height m 18 18 18 18 22 24 32 36 37 40

9 Appendix

137

9.8.2 PV INPUT INFORMATION

Table 47: Installed PV array cost per kW investigation

Ratio

(%) $/kW Resource

Module 37% 1690 Amorphous BRETT

Inverter 13% 570 6kW SMA Sunny Mini central with transformer

Other materials 18% 800 BRETT Email

Installation labour 11% 500 BRETT Email 500 assumed for remote

Others (Regulatory compliance, overhead, etc) 22% 1000

100 extra per watt as more module need to be

installed

TOTAL ($/kW) 4560

Ratio

(%) $/kW Resource

Module 45% 2153.23 235W REC Solar

Inverter 9% 450 11kW SMA Sunny Mini Central transformerless

Other materials 17% 800

Installation labour 9% 450


TOTAL ($/kW) 4753.23

Ratio

(%) $/kW Resource

Module 33% 1300 CEEG 250W Mono Panels (360deals)





TOTAL ($/kW) 3900

Ratio

(%) $/kW Resource

Module 26% 1000 XH 250W Mono Panels (360deals)





TOTAL ($/kW) 3600

9 Appendix

138

9.8.3 LARGE-SCALE GENERATION CERTIFICATES (LGCS) ASSUMPTION

(http://www.nges.com.au/general/australian-carbon-market.htm)

Figure 85: LGCs‟ cost history from October 2010 to October 2011

A live value of the LGC‟s cost is available on the clean energy council web page which can

be accessed using the link below:

http://www.cleanenergycouncil.org.au/cec.html

9.8.4 NATURAL GAS AND DIESEL CARBON CONTENT CALCULATION

Table 48: Natural gas and diesel carbon content

Natural gas Diesel

Energy content (GJ/m3) 0.0387 Energy content (GJ/kL) 38.6

Emission Factor (kg CO2/GJ) Total

Emission Factor (kg

CO2/GJ) Total

CO2 51.2 1.98E-03 69.2 0.00267112

CH4 0.1 3.87E-06 0.1 0.00000386

NO2 0.03 1.16E-06 0.2 0.00000772

Total (t(CO2)/m3) 1.99E-03 Total (t(CO2)/L) 2.68E-03

http://www.nges.com.au/general/australian-carbon-market.htm

http://www.cleanenergycouncil.org.au/cec.html

9 Appendix

139

9.8.5 RE POTENTIAL IN THE CURRENT POWER SYSTEM

PV + Current Power system analysis


Different size of PV array were modelled with different project life. This was done to assess

when and which PV array size becomes more economic than the current power system.

As it can be observed in Figure 92, PV only becomes competitive with the current system if

the project life is 13 years or above. For a project life of 15 and 18 years the most

economically viable PV array size is around 120 and 150 kW respectively.

Figure 86: NPC analysis of different PV array sizes with a project life of 5 years


$0.0E+0

$5.0E+5

$1.0E+6

$1.5E+6

$2.0E+6

$2.5E+6

0 100 200 300 400

PV array (kW)

NPV ($)

PV (5)

Gen (5)

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

0 100 200 300 400

PV array (kW)

NPV ($)

Gen(7)

PV (7)

9 Appendix

140



$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

0 100 200 300 400

PV array (kW)

NPV ($)

Gen(9)

PV (9)

$2,350,000.00

$2,400,000.00

$2,450,000.00

$2,500,000.00

$2,550,000.00

$2,600,000.00

$2,650,000.00

$2,700,000.00

$2,750,000.00

$2,800,000.00

$2,850,000.00

0 100 200 300 400

PV array (kW)

NPC ($)

Gen(12)

PV (12)

$2,700,000.00

$2,750,000.00

$2,800,000.00

$2,850,000.00

$2,900,000.00

$2,950,000.00

$3,000,000.00

$3,050,000.00

0 100 200 300 400

PV array (kW)

NPC ($)

Gen (15)

PV (15)

9 Appendix

141



Figure 92: NPC of different PV array size versus project life

$2,900,000.00

$2,950,000.00

$3,000,000.00

$3,050,000.00

$3,100,000.00

$3,150,000.00

$3,200,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen (18)

PV (18)

$2,100,000.00

$2,200,000.00

$2,300,000.00

$2,400,000.00

$2,500,000.00

$2,600,000.00

$2,700,000.00

$2,800,000.00

$2,900,000.00

$3,000,000.00

$3,100,000.00

10 11 12 13 14 15 16 17 18

Project life (yrs)

NPC ($)

GEN

PV (50kW)

PV (100kW)

PV (150kW)

PV (200kW)

PV (250kW)

PV (300kW)

9 Appendix

142

- Project starting January 2014. 2016 and 2018 with a sensitivity analysis on the project

life:

2014 Analysis:



$1,300,000.00

$1,400,000.00

$1,500,000.00

$1,600,000.00

$1,700,000.00

$1,800,000.00

$1,900,000.00

$2,000,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPV ($)

PV (5)

Gen (5)

$1,750,000.00

$1,800,000.00

$1,850,000.00

$1,900,000.00

$1,950,000.00

$2,000,000.00

$2,050,000.00

$2,100,000.00

$2,150,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(7)

PV (7)

9 Appendix

143



$2,050,000.00

$2,100,000.00

$2,150,000.00

$2,200,000.00

$2,250,000.00

$2,300,000.00

$2,350,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(9)

PV (9)

$2,400,000.00

$2,420,000.00

$2,440,000.00

$2,460,000.00

$2,480,000.00

$2,500,000.00

$2,520,000.00

$2,540,000.00

$2,560,000.00

$2,580,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(12)

PV (12)

9 Appendix

144

2016 Analysis:

For a project starting on January 2016, it can be seen that PV becomes economically feasible

if the project life is around 6 years or more.



$1,400,000.00

$1,450,000.00

$1,500,000.00

$1,550,000.00

$1,600,000.00

$1,650,000.00

$1,700,000.00

$1,750,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

PV (5)

Gen (5)

$1,780,000.00

$1,800,000.00

$1,820,000.00

$1,840,000.00

$1,860,000.00

$1,880,000.00

$1,900,000.00

$1,920,000.00

$1,940,000.00

$1,960,000.00

$1,980,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(7)

PV (7)

9 Appendix

145

v


2018 Analysis:

For a project starting on January 2018, it can be seen that PV becomes economically feasible

if the project life is around 5 years or more.


$2,060,000.00

$2,080,000.00

$2,100,000.00

$2,120,000.00

$2,140,000.00

$2,160,000.00

$2,180,000.00

$2,200,000.00

$2,220,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(9)

PV (9)

$1,500,000.00

$1,550,000.00

$1,600,000.00

$1,650,000.00

$1,700,000.00

$1,750,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

PV (5)

Gen (5)

9 Appendix

146



- Project starting January 2012 with a sensitivity analysis on the load:

Examining the figures below, it can be seen that the load does not affect the viability of PV

technology when connected to the current power system.

$1,820,000.00

$1,840,000.00

$1,860,000.00

$1,880,000.00

$1,900,000.00

$1,920,000.00

$1,940,000.00

$1,960,000.00

$1,980,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(7)

PV (7)

$2,100,000.00

$2,150,000.00

$2,200,000.00

$2,250,000.00

$2,300,000.00

$2,350,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC ($)

Gen(9)

PV (9)

9 Appendix

147

Project life of 8 years:

Figure 103: NPC analysis of different PV array sizes with a load factor of 1


$1,700,000.00

$1,800,000.00

$1,900,000.00

$2,000,000.00

$2,100,000.00

$2,200,000.00

$2,300,000.00

$2,400,000.00

$2,500,000.00

$2,600,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC (PL: 8years)

Gen (1)

PV (1)

$5,500,000.00

$5,600,000.00

$5,700,000.00

$5,800,000.00

$5,900,000.00

$6,000,000.00

$6,100,000.00

0 100 200 300 400

PV array (kW)

NPC (PL: 8years)

Gen (3)

PV (3)

9 Appendix

148




$10,500,000.00

$11,000,000.00

$11,500,000.00

$12,000,000.00

$12,500,000.00

$13,000,000.00

0 500 1000 1500

PV array (kW)

NPC (PL: 8years)

Gen (6)

PV (6)

$2,350,000.00

$2,400,000.00

$2,450,000.00

$2,500,000.00

$2,550,000.00

$2,600,000.00

$2,650,000.00

$2,700,000.00

$2,750,000.00

$2,800,000.00

$2,850,000.00

0 50 100 150 200 250 300 350

PV array (kW)

NPC (PL: 12years)

Gen (1)

PV (1)

9 Appendix

149



Wind turbine + current power system analysis:


Only three configuration of wind turbine can be modelled per wind turbine in REMAX.

These were modelled with different project life. This was done to assess when and which

wind turbine configurations become more economic than the current power system.

$7,240,000.00

$7,250,000.00

$7,260,000.00

$7,270,000.00

$7,280,000.00

$7,290,000.00

$7,300,000.00

$7,310,000.00

$7,320,000.00

$7,330,000.00

$7,340,000.00

0 100 200 300 400

PV array (kW)

NPC

Gen (3)

PV (3)

$14,400,000.00

$14,500,000.00

$14,600,000.00

$14,700,000.00

$14,800,000.00

$14,900,000.00

$15,000,000.00

$15,100,000.00

$15,200,000.00

$15,300,000.00

0 200 400 600 800 1000 1200

PV array (kW)

NPC

Gen (6)

PV (6)

9 Appendix

150

It can be seen that the wind power becomes economically viable when the project life around

12 or more.


years


years

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

System

NPV ($) (5)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00

NPV ($) (9)

9 Appendix

151


years


years

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00

NPC (Project life: 12 years)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

152


years

- Project starting January 2014. 2016 and 2018 with a sensitivity analysis on the project

life:

2014 analysis:

Figure 114 : NPC analysis of wind turbine configurations with a project life of 5 years

$-

$1,000,000.00

$2,000,000.00

$3,000,000.00

$4,000,000.00

$5,000,000.00

$6,000,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

9 Appendix

153

Figure 115: NPC analysis of wind turbine configurations with a project life of 7 years


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00

NPV ($)

9 Appendix

154



$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

155



2016 analysis:

For a project starting on January 2016, it can be observed that the wind power becomes

economically viable than the current power system when the project life around 12 or more.

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

156



$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

9 Appendix

157



$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

158



$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

159


2018 analysis:

For a project starting on January 2018, it can be seen that the wind power becomes

economically viable than the current power system when the project life around 9 or more.


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

9 Appendix

160



$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00

NPV ($)

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00


9 Appendix

161



2018 analysis:

- Project starting January 2012 with a sensitivity analysis on the load:

It can be observed in the figures below that the wind power becomes economically viable

when the project life around 12 or more and load factor of 3 or more.

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00


9 Appendix

162


Figure 133: NPC analysis of different wind turbine configurations with a load factor of 1


$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00

NPC

$-

$1,000,000.00

$2,000,000.00

$3,000,000.00

$4,000,000.00

$5,000,000.00

$6,000,000.00

$7,000,000.00

$8,000,000.00

NPC

9 Appendix

163




$10,000,000.00

$10,500,000.00

$11,000,000.00

$11,500,000.00

$12,000,000.00

$12,500,000.00

$13,000,000.00

NPC

$- $500,000.00

$1,000,000.00 $1,500,000.00 $2,000,000.00 $2,500,000.00 $3,000,000.00 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00

NPC

9 Appendix

164



Wind turbine(s) + PV array + current power system analysis:

- Project starting on January 2012 with a sensitivity analysis on project life:

For a project starting in January 2012, a system composed with different wind turbine(s), PV

arrays and the current power system starts to become competitive with the current p[ower

system for a project life of at least12 years or above.

$6,400,000.00 $6,600,000.00 $6,800,000.00 $7,000,000.00 $7,200,000.00 $7,400,000.00 $7,600,000.00 $7,800,000.00 $8,000,000.00 $8,200,000.00 $8,400,000.00 $8,600,000.00

NPC

$13,800,000.00 $14,000,000.00 $14,200,000.00 $14,400,000.00 $14,600,000.00 $14,800,000.00 $15,000,000.00 $15,200,000.00 $15,400,000.00 $15,600,000.00

NPC

9 Appendix

165


life of 12 years


life of 15 years

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

$3,500,000.00

Generator only

PV50 + FWS100 x 1

PV50 + FWS100 x 2

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPC

$2,400,000.00

$2,500,000.00

$2,600,000.00

$2,700,000.00

$2,800,000.00

$2,900,000.00

$3,000,000.00

$3,100,000.00

$3,200,000.00

PV50 + FWS100 x 2

PV50 + FWS100 x 1

Generator only

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPC

9 Appendix

166


life of 18 years

Wind turbine + current power system analysis:


life of 5 years

$2,600,000.00

$2,700,000.00

$2,800,000.00

$2,900,000.00

$3,000,000.00

$3,100,000.00

$3,200,000.00

$3,300,000.00

PV50 + FWS100 x 2

PV50 + FWS100 x 1

PV200 + FWS50 x 1

Generator only

PV300 + FWS50 x 1

NPC

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

Generator only

PV50 + FWS100 x 1

PV50 + FWS100 x 2

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPV ($)

9 Appendix

167


life of 7 years


life of 8 years

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

Generator only

PV50 + FWS100 x 1

PV50 + FWS100 x 2

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPV ($)

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

Generator only

PV50 + FWS100 x 1

PV50 + FWS100 x 2

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPV ($)

9 Appendix

168


life of 9 years

Overall analysis:

Figure 146: NPC analysis of different system configuration with a project life of 5 years

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

Generator only

PV50 + FWS100 x 1

PV50 + FWS100 x 2

PV200 + FWS50 x 1

PV300 + FWS50 x 1

NPV ($)

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

NPV ($)

9 Appendix

169



$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

NPV ($)

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

NPV ($)

9 Appendix

170


9.8.6 STANDALONE ANALYSIS

Figure 150: HOMER output screen shot for project starting in January 2012

$-

$500,000.00

$1,000,000.00

$1,500,000.00

$2,000,000.00

$2,500,000.00

$3,000,000.00

NPV ($)

9 Appendix

171




9 Appendix

172

- Project starting January 2012 with a sensitivity analysis on the load and project life:

The appropriate standalone diesel configuration was first identified for the corresponding

load and then used for the simulation.

The MMG village load was multiplied by one, three and six to model a 150, 450 and 900 man

camp respectively.


daily load of 8568 kWh


daily load of 8568 kWh (Graph representation)

9 Appendix

173


daily load of 17136 kWh


daily load of 17136 kWh (Graph representation)

9 Appendix

174

9.9 GEOTHERMAL AIR CONDITIONING INFORMATION

A list of the major geothermal heat pump manufacturers researched and used for this project

are available below:

- Northern Heat Pump (USA, Canada)

- Water Furnace (AUS geothermal WA supplier)

- Climate Master (USA, AUS)

- Geofurnace Heat Pump (Michigan)

- Florida Heat Pump (Florida)

- McQuay Heat Pump (NSW Australia)

- Trane Heat Pump (USA, NSW Australia)

- Maritime Geothermal Heat Pump (Canada, Europe, USA)

- Hydron Heat Pump (USA)

- Dimplex Heat Pump (UK)

9.10 MONITORING EQUIPMENT INFORMATION

Table 49: Monitoring equipment information (OneTemp, 2011)

Device Name Code Quantity Purpose

HOBO U30 U30-ETH-000-05-S100 6

Data Logger system where data

are recorded and then

transmitted

Trans, Mini

AC split, 50

amp 0.333 vac

CT

T-MAG-0400-50 12 Sensor to undertake current

measurements below 50 amps

Magnelab 0 –

100 AMP T-MAG-SCT-100 12

Sensor to undertake current


Magnelab 0 –




Magnelab 0 –




Ethernet to

radio signal NANOSTATION-LOCO2 7

Remote Ethernet Modem use to

transmit and receive the

9 Appendix

175

modem

LOCO2

collected data from the HOBO

U30 onto the sever

Temperature/

RH Smart

Sensor

S-THB-M002

1

Sensor use to measure

temperature and humidity

Electronic

Switch Pulse

Input Adapter

S-UCC-M006 5

Device used to transfer pulse

sensor output data to the HOBO

U30 logger

Pulse Sensor

probes n/a 5

Sensor use to measure water use

through a pulse that is

transferred to the Electronic

Switch Pulse Input Adapter

which transfer the data to the

HOBO U30 logger

9 Appendix

176

9.11 SOFTWARE INVESTIGATION RESULTS

Figure 158: SimaPro “Wooden Shed” tutorial output summary (SimaPro, 2011)

Figure 159: GaBi “Steel Paper Clip” tutorial plan (GaBi, 2011)

9 Appendix

177

9.12 MMG VILLAGE ENERGY AUDIT

Cell coloured in yellow were assumed and need to be confirmed using the drawing plans.

Table 50: Outdoor energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Parking light 10

Sodium

holide

Foot path

light 3 20

Table 51: Laundry energy audit

Device

Number of

device (Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Hpot water

system 1 3600

315L

Outdoor

light 2

Indoor light 12 36

Extract fans 5

"HPM"

Washing

machine 8 650

"MayTag" Commercial

Laundry Washer

Drier 8 4200

240V x 20A circuit "F.2

Costello and Co"

9 Appendix

178

Table 52: Donga energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Hot water

system 1

AC 4

Cooling: 2.5kW,

Heating: 3.4kW

Outdoor light 2

Indoor light 8 36

Bed light 4

TV 4

Fridge 4

295 kW/year

Extract fan 4

Table 53: Administration energy audit

ADMINISTRATION

Device

Number of

device (Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Reception (Rear)

Cooling cabinet 1 20.2

Hot Water Boiling

Unit 1 2447

Biriko, occasionally used

Desktop PC 3

Out of use

Radio

Coomunication 1 7

Charger

Indoor light 24 36

Exit light

20

(350 - 400 Lux)

Reception (Front)

9 Appendix

179

Fridge 1

"Skope", stand by 62.5W,

working 360W, (2degC)

Till

Desktop PC

Printer

Laminator

Exit light 1 20

Indoor light 4 36

Camp manager office

Indoor light 4 36

Laptop 2

Desktop PC 2

Communication room

Indoor light 2 36

Internet Modems

and Switches ? ? ? ?

Outside

Outside light 2

AC1 (5kW) 6

Cooling: 5kW, Heating 6kW

AC2 (2.5kW) 1

Cooling: 2.5kW, Heating:

3.4kW

Table 54: Toilet energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week)

Comment

s

Outside

light 2

84.00

Ladies

Inside light 4 36 168.00

Extract fan 2

168.00

Men


Extract fan 2

168.00

9 Appendix

180

Disabled

Inside light ? ? ? Closed

Extract fan ? ? ? Closed

Table 55: Recreational room energy audit

Device

Number of

device (Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Outside light 1

84.00


Hot Water

Boiling Unit 1 2600

"Birko"

Fridge 1 820 168.00

"Hisense", empty, rarely

used, Standby: 8W

Desktop 2

AC 4

Cooling: 5kW, Heating: 6kW

Table 56: Gymnasium energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

AC 4

Cooling: 5kW, Heating:

6kW

Outside light 1

84.00


Water cooler 2 175

"Zip, economaster"

Walker 2

"SportArt Fitness"

Model: E870

Running

Machine 3

"SportArt Fitness"

Model: T652

Rowing

Machine 1

"Concept 2"

9 Appendix

181

Table 57: Kitchen energy audit

Device

Number of

device

(Unit)

Power

use

(W/unit)

Time of use

(Hrs/week) Comments

Dry Mess

Inside light 74 36

UV insect

killer 3 40

Bain Marie

(Cool) 3 1260 84.00 Standby: 215 W

Small Heat

Bain Marie 1

1720-

2047

In use at night shift only

Soup Heater 1 475-580

In use at night shift only

Hot Water

Boiling

System 2 2600

Milk Cooler 1 125

Standby: 7 W

Ice cream

servery 1 290

Fridge

(2doors) 1 550 168.00 Full, Standby: 7 W

Fridge

(1door) 1 350 168.00 "Topon", Model: ldsigdcb

Drink

dispencer 3 190 168.00

Toaster 2 3600

"ROBAND conveyor toaster"

Exit light 3 10 168.00

Plate

Warmer 1 603 168.00

9 Appendix

182

Air curtin 4 660

2 unit : 168h/w and 2unit : Shift time

only

Wet Mess

Inside light 14 36

Food light

heater 2 250

Hot Bain

Marie 1 10000

20A x 500V power supply, for food

dinner (Spagheti)

Frier 2

4hrs/day, 2-3day/week, "Goldstein,

Rapid Fry"

Oven and

Hub 1

Hub: 16-18kW, Oven: 6-4kW, 2 x 8.4kW,

4 - 5 h/day

Hot Plat 1

3 x

6000W

Low to keep soup warm, 50% use

Oven and

Steamer 1

4 - 5 h/day

Dishwasher 1

16 h/day, "Eswood", Model: ES100EV,

Massive kettle, "Combimaster Rational"

Exit light 4

Radio 1 15 168.00

Fridge

(2doors) 1 550 168.00 Full, Standby: 7 W, Same as Dry Mess

Slicer 1 240

1 - 0.5

hr/day "SIRMAN"

Potatoes

rambler 1 750 1 - 5 h/day

Cooker 2 12000 1h/day "Goldstein"

Oven 1

3 x 4400, 2h/day

Mixer 1 1500

Rarely used

Microwave 1 550

Rarely used

Inside light 46 36

Inside light

(Cool RoomO 16 0

UV insect 3

9 Appendix

183

killer

Green light 1 24

Vaccum Fan 16

36W light

Extract Fan 12

Outside

CoolRoom

Motor 1 2

"BITZER CS Series, Model: 4ec42-c53-4p

CoolRoom

Motor 2 1

"BITZER CS Series, Model: 2jc072-csi-4p

AC1 (3.5kW) 1

Cooling: 3.5kW, Heating: 4.8kW

AC2 (9.4kW) 13

Cooling: 9.4kW, Heating: 10kW

AC3 (5kW) 3

Cooling: 5kW, Heating: 6kW

Outside light 9

Hot Water

System 2 3600

Rated power: 3.6kW, Electric booster

315ltrs

Table 58: WTP energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

Pump (4 and

5) 2 7500

Control

System 1

Fan + led

lights

Table 59: WWTP energy audit

Device

Number of

device (Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

AC 1

Cooling: 3.5kW, Heating:

4.8kW, Set on 19degC

Pump (1 and 2) 2

1 - 5kW

Inside light 6 36

Control system 1

Touch screen

9 Appendix

184

Small compressor 1

1 - 2 kW, Rarely used

Green warnning light

(Outside) 2

168.00

Aerator

168.00

More pumps and electrici

devices unaccessible

6.00

Table 60: Ice room energy audit

Device

Number of device

(Unit)

Power use

(W/unit)

Time of use

(Hrs/week) Comments

AC 1

Cooling: 5kW,

Heating: 6kW

Outoo fan 2 140

Ice maker

machine 2 3000

Water cooler

machine 1 1500

Inside light 4 36

Breathaliser

(Alcohol) 1

Air curtin 1 86

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