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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
viii
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 38: NPC analysis of different systems‟ configuration for a project starting in January
2014 with different project life. ............................................................................................... 54
Figure 39: NPC analysis of different systems‟ configuration for a project starting in January
2016 with different project life. ............................................................................................... 55
Figure 40: NPC analysis of different systems‟ configuration for a project starting in January
2018 with different project life. ............................................................................................... 55
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 44: CO2 emissions comparison for a project starting in January 2014 ......................... 62
Figure 45: CO2 emissions comparison for a project starting in January 2016 ......................... 63
Figure 46: CO2 emissions comparison for a project starting in January 2018 ......................... 65
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
Figure 63: Capital cost sensitivity analysis for the 50kW system operating 10 hours a day
(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
Figure 77: Monthly average wind speed seasonal variation at 10m above ground surface at
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
Figure 80: Frequency distribution wind speed at 50m above ground surface at Mount Magnet
(NASA, 2011) ........................................................................................................................ 117
Figure 81: Wind speed cumulative probability function at 50m above ground level at Mount
Magnet (NASA, 2011) ........................................................................................................... 117
Figure 82: Weibull distribution factor estimation graph of wind speed 50m above ground
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 87: NPC analysis of different PV array sizes with a project life of 7 years ............... 139
Figure 88: NPC analysis of different PV array sizes with a project life of 9 years ............... 140
Figure 89: NPC analysis of different PV array sizes with a project life of 12 years ............. 140
x
Figure 90: NPC analysis of different PV array sizes with a project life of 15 years ............. 141
Figure 91: NPC analysis of different PV array sizes with a project life of 18 years ............. 141
Figure 92: NPC of different PV array size versus project life ............................................... 141
Figure 93: NPC analysis of different PV array sizes with a project life of 5 years ............... 142
Figure 94: NPC analysis of different PV array sizes with a project life of 7 years ............... 142
Figure 95: NPC analysis of different PV array sizes with a project life of 9 years ............... 143
Figure 96: NPC analysis of different PV array sizes with a project life of 12 years ............. 143
Figure 97: NPC analysis of different PV array sizes with a project life of 5 years ............... 144
Figure 98: NPC analysis of different PV array sizes with a project life of 7 years ............... 144
Figure 99: NPC analysis of different PV array sizes with a project life of 9 years ............... 145
Figure 100: NPC analysis of different PV array sizes with a project life of 5 years ............. 145
Figure 101: NPC analysis of different PV array sizes with a project life of 7 years ............. 146
Figure 102: NPC analysis of different PV array sizes with a project life of 9 years ............. 146
Figure 103: NPC analysis of different PV array sizes with a load factor of 1 ....................... 147
Figure 104: NPC analysis of different PV array sizes with a load factor of 3 ....................... 147
Figure 105: NPC analysis of different PV array sizes with a load factor of 6 ....................... 148
Figure 106: NPC analysis of different PV array sizes with a load factor of 1 ....................... 148
Figure 107: NPC analysis of different PV array sizes with a load factor of 3 ....................... 149
Figure 108: NPC analysis of different PV array sizes with a load factor of 6 ....................... 149
Figure 109: NPC analysis of different wind turbine configurations with a project life of 5
years ....................................................................................................................................... 150
Figure 110: NPC analysis of different wind turbine configurations with a project life of 9
years ....................................................................................................................................... 150
Figure 111: NPC analysis of different wind turbine configurations with a project life of 12
years ....................................................................................................................................... 151
Figure 112: NPC analysis of different wind turbine configurations with a project life of 15
years ....................................................................................................................................... 151
Figure 113: NPC analysis of different wind turbine configurations with a project life of 18
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 116: NPC analysis of wind turbine configurations with a project life of 8 years ...... 153
Figure 117: NPC analysis of wind turbine configurations with a project life of 9 years ...... 154
Figure 118: NPC analysis of wind turbine configurations with a project life of 12 years .... 154
Figure 119: NPC analysis of wind turbine configurations with a project life of 15 years .... 155
Figure 120: NPC analysis of wind turbine configurations with a project life of 18 years .... 155
Figure 121: NPC analysis of wind turbine configurations with a project life of 5 years ...... 156
Figure 122: NPC analysis of wind turbine configurations with a project life of 7 years ...... 156
Figure 123: NPC analysis of wind turbine configurations with a project life of 8 years ...... 157
Figure 124: NPC analysis of wind turbine configurations with a project life of 9 years ...... 157
Figure 125: NPC analysis of wind turbine configurations with a project life of 12 years .... 158
Figure 126: NPC analysis of wind turbine configurations with a project life of 15 years .... 158
Figure 127: NPC analysis of wind turbine configurations with a project life of 18 years .... 159
Figure 128: NPC analysis of wind turbine configurations with a project life of 5 years ...... 159
xi
Figure 129: NPC analysis of wind turbine configurations with a project life of 7 years ...... 160
Figure 130: NPC analysis of wind turbine configurations with a project life of 8 years ...... 160
Figure 131: NPC analysis of wind turbine configurations with a project life of 9 years ...... 161
Figure 132: NPC analysis of wind turbine configurations with a project life of 12 years .... 161
Figure 133: NPC analysis of different wind turbine configurations with a load factor of 1 . 162
Figure 134: NPC analysis of different wind turbine configurations with a load factor of 3 . 162
Figure 135: NPC analysis of different wind turbine configurations with a load factor of 6 . 163
Figure 136: NPC analysis of different wind turbine configurations with a load factor of 1 . 163
Figure 137: NPC analysis of different wind turbine configurations with a load factor of 3 . 164
Figure 138: NPC analysis of different wind turbine configurations with a load factor of 6 . 164
Figure 139: NPC analysis of different wind turbine and PV array configuration with a project
life of 12 years ....................................................................................................................... 165
Figure 140: NPC analysis of different wind turbine and PV array configuration with a project
life of 15 years ....................................................................................................................... 165
Figure 141: NPC analysis of different wind turbine and PV array configuration with a project
life of 18 years ....................................................................................................................... 166
Figure 142: NPC analysis of different wind turbine and PV array configuration with a project
life of 5 years ......................................................................................................................... 166
Figure 143: NPC analysis of different wind turbine and PV array configuration with a project
life of 7 years ......................................................................................................................... 167
Figure 144: NPC analysis of different wind turbine and PV array configuration with a project
life of 8 years ......................................................................................................................... 167
Figure 145: NPC analysis of different wind turbine and PV array configuration with a project
life of 9 years ......................................................................................................................... 168
Figure 146: NPC analysis of different system configuration with a project life of 5 years .. 168
Figure 147: NPC analysis of different system configuration with a project life of 7 years .. 169
Figure 148: NPC analysis of different system configuration with a project life of 8 years .. 169
Figure 149: NPC analysis of different system configuration with a project life of 9 years .. 170
Figure 150: HOMER output screen shot for project starting in January 2012 ...................... 170
Figure 151: HOMER output screen shot for project starting in January 2014 ...................... 171
Figure 152: HOMER output screen shot for project starting in January 2016 ...................... 171
Figure 153: HOMER output screen shot for project starting in January 2018 ...................... 171
Figure 154: HOMER output screen shot for project starting in January 2012 and an average
daily load of 8568 kWh.......................................................................................................... 172
Figure 155: HOMER output screen shot for project starting in January 2012 and an average
daily load of 8568 kWh (Graph representation) .................................................................... 172
Figure 156: HOMER output screen shot for project starting in January 2012 and an average
daily load of 17136 kWh........................................................................................................ 173
Figure 157: HOMER output screen shot for project starting in January 2012 and an average
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 21: HOMER output summary for project starting in January 2014 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW)) ....................................... 61
Table 22: HOMER output summary for project starting in January 2016 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW)) ....................................... 63
Table 23: HOMER output summary for project starting in January 2018 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW)) ....................................... 64
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
Table 33: 50kW GSHP system payback period estimation comparison with a current 50kW
AC system operating 10hours a day ........................................................................................ 89
Table 34: Investigated software and comments ....................................................................... 93
Table 35: Weibull distribution factor graph calculation ........................................................ 113
Table 36: Monthly and annual average wind speed at 10m above ground surface at Mount
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
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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
3 MMG Village RE 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
D2 - Cummins 0.7 Diesel unknown 30
D3 - 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
G3 EnGen Deutz 1.26 Gas 38 30
G4 EnGen Deutz 1.26 Gas 38 30
G5 EnGen Deutz 1.26 Gas 38 30
G6 EnGen Deutz 1.26 Gas 38 30
Figure 8: Mount Magnet gold mine power system and loads
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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).
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
19
Figure 12: Australia‟s rainfall map (Kuwahata et al. 2010)
Figure 13: MM topographic map (One line represents 20m elevation) (Google Maps, 2011)
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
22
Table 7: Monthly and annual average wind speed at 10m above ground surface at Mount
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
Figure 15: Monthly average wind speed seasonal variation at 10m above ground surface at
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
24
Figure 18: Frequency distribution wind speed at 10m above ground surface at Mount Magnet
(BOM, 2011)
Figure 19: Wind speed cumulative probability function at 10m above ground level at Mount
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
3 MMG Village RE Power System
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
Figure 20: Weibull distribution factor estimation graph of wind speed 10m above ground
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
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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).
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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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)
3 MMG Village RE Power System
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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.
3 MMG Village RE Power System
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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.
3 MMG Village RE Power System
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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).
3 MMG Village RE Power System
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
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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.
3 MMG Village RE Power 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.
3 MMG Village RE Power System
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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
3 MMG Village RE Power System
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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
3 MMG Village RE Power System
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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 $/(yr.WT) 19500 10250
Life time yrs 20 20
Hub height m 32 24
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For each wind turbines investigated in this project, the corresponding power curve was used.
Only 10 wind turbines were investigated as no other manufacturers provided appropriate cost
estimations for their products. The assumptions made to estimate the installed cost of each
wind turbine were assisted by Antony Piccinini. Other wind turbine input information is
available in the appendix section 9.7 of this report. The ten wind turbines investigated in this
project are listed below from smallest to largest:
- Skystream (2.4kW)
- Evance (5kW)
- Gilong (10kW)
- Gaia (11kW)
- WestWind (20kW)
- Four Wind Seasons (FWS) (50kW)
- Four Wind Seasons (FWS) (100kW)
- Four Wind Seasons (FWS) (200kW)
- Enercon (E) (330kW)
- Enercon (E) (600kW)
Figure 32 below illustrates the cost of each wind turbine investigated per installed Watt
versus their capacity. It can be observed that the bigger the wind turbine the lower the cost
per installed Watt.
Figure 31: Cost per installed Watt versus wind turbine capacity.
0
2
4
6
8
10
12
0 100 200 300 400 500 600
Cost ($/W)
Wind Turbine capacity (kW)
Cost per installed Watt versus wind turbine capacity
3 MMG Village RE Power System
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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
3 MMG Village RE Power System
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 ($)
- Power cost ($/kWh)
- RE fraction (%)
- Diesel use (L/yr)
- Generator operation
(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 ($)
- Power cost ($/kWh)
- RE fraction (%)
- Diesel use (L/yr)
- Generator operation
(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
3 MMG Village RE Power System
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%
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
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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.
3 MMG Village RE 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
($)
System configuration
NPC difference with current power system per tonne of CO2 emissions offset
3 MMG Village RE Power System
50
III.ii.b WIND TURBINE(S) + PV ARRAY + CURRENT POWER SYSTEM SELECTION
To select the most appropriate system configuration, the same method as when selecting the
wind turbines was used. . Figure 34 illustrates the NPC difference with the current power
system per tonne of CO2 emission offset for a project life of 8 years. Hence, it can be
observed that the most suitable system configurations for this case is a 50 kW PV array with
one and two 100kW FWS wind turbines, 200 and 330kW PV array with one FWS wind
turbine. These configurations were then used to assess the economic viability of these
systems under different project lives.
Figure 33: NPC difference with the current power system per tonne of CO2 emissions offset
(Project life of 8 years)
III.ii.c ANALYSIS
As it can be observed in Figure 35 below, retrofitting RE power systems with the current
power system begins to be economically viable if the project life is 13 years or more.
0
500
1000
1500
2000
2500
($)
System configuration
NPC difference with the current power system per tonne of CO2 emission offset
3 MMG Village RE Power System
51
Figure 34: NPC analysis of different systems‟ configuration for a project starting in January
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
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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
2016: Diesel cost: June 2012 cost x (1 + 0.08)2016-2012
= 1.20 x (1.08)4 = 1.64 $/L
2018: Diesel cost: June 2012 cost x (1 + 0.08)2016-2012
= 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
3 MMG Village RE Power System
54
Carbon price use:
2014: January 2012 Carbon price x (1 + 0.03)2014-2012
= 23 x (1.03)2 = 24.4 $/t(CO2)
2016: January 2012 Carbon price x (1 + 0.03)2016-2012
= 23 x (1.03)4 = 25.9 $/t(CO2)
2018: January 2012 Carbon price x (1 + 0.03)2016-2012
= 23 x (1.03)6 = 27.46 $/t(CO2)
Figure 37: NPC analysis of different systems‟ configuration for a project starting in January
2014 with different project life.
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 (
$)
Project life (years)
NPC analysis (Project starting January 2014)
Current Power System (Ideal)
Current Power System (Ideal) + RE
Current Power System (80% Ideal)
3 MMG Village RE Power System
55
Figure 38: NPC analysis of different systems‟ configuration for a project starting in January
2016 with different project life.
Figure 39: NPC analysis of different systems‟ configuration for a project starting in January
2018 with different project life.
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 (
$)
Project life (years)
NPC analysis (Project starting January 2016)
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 (
$)
Project life (years)
NPC analysis (Project starting January 2018)
Current Power System (Ideal)
Current Power System (Ideal) + RE
Current Power System (80% Ideal)
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
57
Table 20: HOMER output summary for project starting in January 2012 (Generators: low
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
8 Generators + FWS(100kW) x 2 $2,214,831.00 51% 216.53
9 Generators + FWS(100kW) x 2 $2,335,188.00 51% 216.53
10 Generators + FWS(100kW) x 2 $2,447,336.00 51% 216.53
11 Generators + FWS(100kW) x 3 $2,531,653.00 70% 340.01
12 Generators + FWS(100kW) x 3 $2,609,152.00 70% 340.01
13 Generators + FWS(100kW) x 3 $2,680,897.00 70% 340.01
14 Generators + FWS(100kW) x 3 $2,747,426.00 70% 340.01
15 Generators + FWS(100kW) x 3 $2,808,845.00 70% 340.01
16 Generators + FWS(100kW) x 3 $2,865,782.00 70% 340.01
17 Generators + FWS(100kW) x 3 $2,918,801.00 70% 340.01
18 Generators + FWS(100kW) x 3 $2,967,913.00 70% 340.01
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
3 MMG Village RE Power System
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 (
$)
Project life (years)
Standalone and current power system NPC analysis for different transmission line length
Current Power System (6 kms)
Current Power System (4 kms)
Current Power System (2 kms)
Standalone Power System (Generators only)
Standalone Power System (Generators + RE)
3 MMG Village RE Power System
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)
3 MMG Village RE Power System
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 = $3400 per kW installed),
is “generator only”.
Figure 42: HOMER output screen shot for project starting in January 2012 with sensitivity
analysis on PV cost and project life
- Project starting January 2014 with a sensitivity analysis on the project life:
In a standalone situation, using projected installed wind turbine and PV array costs for
January 2014, it can be observed in Table 21 that a mix of a few of the FWS 100 kW wind
turbines with the selected diesel generator is more economically viable than the diesel
generator system itself with a project life of 5 years or above. It is also seen that the longer
the project life, the more FWS 100 kW wind turbine become viable.
3 MMG Village RE Power System
61
Table 21: HOMER output summary for project starting in January 2014 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW))
Project
life (Yrs)
Standalone system
configuration Total NPC ($)
Renewable energy
penetration (%)
CO2 offset
(t/yr)
1 Generators $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
5 Generators + FWS(100kW) x 2 $1,939,976.00 51% 221.62
6 Generators + FWS(100kW) x 2 $2,118,433.00 51% 221.62
7 Generators + FWS(100kW) x 3 $2,272,954.00 70% 345.61
8 Generators + FWS(100kW) x 3 $2,393,110.00 70% 345.61
9 Generators + FWS(100kW) x 3 $2,504,061.00 70% 345.61
10 Generators + FWS(100kW) x 3 $2,606,511.00 70% 345.61
11 Generators + FWS(100kW) x 3 $2,701,490.00 70% 345.61
12 Generators + FWS(100kW) x 3 $2,789,557.00 70% 345.61
13 Generators + FWS(100kW) x 3 $2,871,370.00 70% 345.61
14 Generators + FWS(100kW) x 3 $2,946,915.00 70% 345.61
15 Generators + FWS(100kW) x 3 $3,016,672.00 70% 345.61
16 Generators + FWS(100kW) x 3 $3,081,319.00 70% 345.61
17 Generators + FWS(100kW) x 4 $3,137,992.00 83% 423.46
18 Generators + FWS(100kW) x 4 $3,184,677.00 83% 422.98
3 MMG Village RE Power System
62
Figure 43: CO2 emissions comparison for a project starting in January 2014
- Project starting January 2016 with a sensitivity analysis on the project life:
In this situation, in analysing Table 22, it can be noticed that the most appropriate RE hybrid
standalone power system is a 110 kW PV array with the selected generators for a project life
of 4. Nevertheless, it is only for a project life of 4 years that PV is more appropriate than the
FWS 100 kW wind turbines. It is observed that with increasing project lives, the number of
FWS 100 kW wind turbines becomes higher.
100.00
200.00
300.00
400.00
500.00
600.00
700.00
800.00
0 5 10 15 20
t(C
O2)
/yr
Project life (yrs)
C02 emissions comparison (Project starting January 2014)
Current power system
Standalone power system (GEN)
Standalone power system (GEN + RE)
3 MMG Village RE Power System
63
Table 22: HOMER output summary for project starting in January 2016 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW))
Project
life (Yrs)
Standalone system
configuration Total NPC ($) 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
5 Generators + FWS(100kW) x 2 $2,055,249.00 51% 221.62
6 Generators + FWS(100kW) x 3 $2,219,725.00 70% 345.61
7 Generators + FWS(100kW) x 3 $2,361,807.00 70% 345.61
8 Generators + FWS(100kW) x 3 $2,493,025.00 70% 345.61
9 Generators + FWS(100kW) x 3 $2,614,212.00 70% 345.61
10 Generators + FWS(100kW) x 3 $2,726,131.00 70% 345.61
11 Generators + FWS(100kW) x 3 $2,830,644.00 70% 345.61
12 Generators + FWS(100kW) x 4 $2,914,494.00 83% 422.98
13 Generators + FWS(100kW) x 4 $2,988,311.00 83% 422.98
14 Generators + FWS(100kW) x 4 $3,056,770.00 83% 422.98
15 Generators + FWS(100kW) x 4 $3,120,021.00 83% 422.98
16 Generators + FWS(100kW) x 4 $3,178,722.00 83% 422.98
17 Generators + FWS(100kW) x 4 $3,233,280.00 83% 422.98
18 Generators + FWS(100kW) x 4 $3,283,687.00 83% 422.98
Figure 44: CO2 emissions comparison for a project starting in January 2016
100.00
300.00
500.00
700.00
900.00
1 6 11 16
t(C
O2
)/yr
Project life (yrs)
C02 emissions comparison (Project starting January 2016) Current
power system
Standalone power system (GEN)
Standalone power system (GEN + RE)
3 MMG Village RE Power System
64
- Project starting January 2018 with a sensitivity analysis on the project life:
In this situation, very similar observations as a project starting on January 2014 were made.
The only difference is that the number of FWS 100kW wind turbines increased more with
the project life than in a project starting on January 2016. In addition, the most appropriate
RE hybrid standalone power system is also a 110 kW PV array with the selected generators,
but for a project life of 3 instead of 4 for 2016.
Table 23: HOMER output summary for project starting in January 2018 (Generators: low
load cycle REGEN Power generators (150kW + 100kW + 50kW))
Project
life (Yrs)
Standalone system
configuration Total NPC ($) 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
4 Generators + FWS(100kW) x 2 $1,946,472.00 51% 221.62
5 Generators + FWS(100kW) x 3 $2,139,487.00 70% 345.61
6 Generators + FWS(100kW) x 3 $2,307,853.00 70% 345.61
7 Generators + FWS(100kW) x 3 $2,463,467.00 70% 345.61
8 Generators + FWS(100kW) x 3 $2,607,215.00 70% 345.61
9 Generators + FWS(100kW) x 4 $2,721,967.00 83% 422.98
10 Generators + FWS(100kW) x 4 $2,822,253.00 83% 422.98
11 Generators + FWS(100kW) x 4 $2,914,923.00 83% 422.98
12 Generators + FWS(100kW) x 4 $3,000,554.00 83% 422.98
13 Generators + FWS(100kW) x 4 $3,079,784.00 83% 422.98
14 Generators + FWS(100kW) x 4 $3,153,255.00 83% 422.98
15 Generators + FWS(100kW) x 4 $3,221,145.00 83% 422.98
16 Generators + FWS(100kW) x 4 $3,284,260.00 83% 422.98
17 Generators + FWS(100kW) x 4 $3,342,795.00 83% 422.98
18 Generators + FWS(100kW) x 4 $3,396,885.00 83% 422.98
3 MMG Village RE Power System
65
Figure 45: CO2 emissions comparison for a project starting in January 2018
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)
C02 emissions comparison (Project starting January 2018)
Current power system
Standalone power system (GEN)
Standalone power system (GEN + RE)
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
3 MMG Village RE Power System
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
Four Wind Seasons 50kW
Four Wind Seasons 100kW
Four Wind Seasons 200kW
3 MMG Village RE Power System
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.
3 MMG Village RE Power System
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
4 Geothermal Air Conditioning Potential in Mining Villages
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
4 Geothermal Air Conditioning Potential in Mining Villages
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)
4 Geothermal Air Conditioning Potential in Mining Villages
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).
4 Geothermal Air Conditioning Potential in Mining Villages
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).
4 Geothermal Air Conditioning Potential in Mining Villages
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.
4 Geothermal Air Conditioning Potential in Mining Villages
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
4 Geothermal Air Conditioning Potential in Mining Villages
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.
4 Geothermal Air Conditioning Potential in Mining Villages
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.
4 Geothermal Air Conditioning Potential in Mining Villages
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
4 Geothermal Air Conditioning Potential in Mining Villages
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)
4 Geothermal Air Conditioning Potential in Mining Villages
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
4 Geothermal Air Conditioning Potential in Mining Villages
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: $256,152.00
- Annual cooling and heating energy required: 40% of overall load = 435,600 kWh
- Annual water heating load met by GSHP: 16% of overall load = 174,240 kWh
4 Geothermal Air Conditioning Potential in Mining Villages
83
Table 31: Payback period estimation comparison with current system (NPV: Net Present
Value)
Year
No Year
Electricity
Cost
($/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):
Energy saved (kWh) x 87% =
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)
4 Geothermal Air Conditioning Potential in Mining Villages
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: $1,001,256.96)
Figure 59: Annual heating and cooling load sensitivity analysis
0
5
10
15
20
25
30
-60 -40 -20 0 20 40
Pay
bac
k P
erio
d (
Yea
rs)
Capital cost x1000 ($)
Capital cost sensitivity analysis
0
5
10
15
20
25
0 1000000 2000000 3000000 4000000
Pay
bac
k P
erio
d (
Yea
rs)
Energy (kWh)
Sensitivity Analysis of Space Heating and Cooling Load
4 Geothermal Air Conditioning Potential in Mining Villages
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:
- Average yearly COP of 5 for GSHP
- Average yearly COP of 2.7 for current system
- CAPEX of GSHP (50kW system): $185,000.00 (Geothermal WA‟s quote via email)
- CAPEX of current system (50kW air source heat pump system): $30,000.00
- Annual cooling and heating energy required:
Maximum capacity (kW) of AC system x 80% x 20 hours per day x 365 days a year =
50 x 0.8 x 20 x 365 = 292,000kWh
- Annual water heating load met by GSHP:
0
5
10
15
20
25
30
50000 150000 250000 350000 450000 550000
Pay
bac
k P
erio
d (
Yea
rs)
Energy (kWh)
Sensistivity analysis of water heating load
4 Geothermal Air Conditioning Potential in Mining Villages
86
There are two hot water systems installed for the kitchen. As the AC system is rated for
about half of the load, it was estimated that the GSHP system would heat up only one of the
hot water systems. Hence,
Average daily energy use by hot water system (kWh) x 80% x 365 days =
25 (Figure 73) x 0.8 x 365 = 7,300kWh
The payback period in this situation was calculated the same way as the previous section and
using the same discount rate (8%).
Table 32: 50kW GSHP system payback period estimation comparison with a current 50kW
AC system operating 20 hours a day
Year
No Year
Electricity
Cost ($/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
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% =
76,028kWh x 13% = 9,883.64kWh produced from Diesel
Energy produce from diesel (kWh) x Heat rate diesel (L/hWh) x Diesel carbon
content (t(CO2)/L) =
9883.64 x 0.26 x 0.002683 = 6.9 t(CO2)
4 Geothermal Air Conditioning Potential in Mining Villages
87
Carbon emission from Gas (Values obtained from assumptions made in REMAX):
Energy saved (kWh) x 87% =
76,028kWh x 87% = 66,144.36kWh produced from Gas
x
x Gas carbon content (t(CO2)/m
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
tonnes of carbon dioxide emissions. The payback period in this case is 11 years.
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
Figure 61: Capital cost sensitivity analysis for the 50kW system operating 20 hours a day
(Capital cost: $185,000)
6
7
8
9
10
11
12
13
14
15
-60 -40 -20 0 20 40 60
Pay
bac
k P
erio
d (
Yea
rs)
Capital cost x1000 ($)
Capital cost sensitivity analysis
4 Geothermal Air Conditioning Potential in Mining Villages
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:
- Average yearly COP of 5 for GSHP
- Average yearly COP of 2.7 for current system
- CAPEX of GSHP (50kW system): $185,000.00 (Geothermal WA‟s quote via email)
- CAPEX of current system (50kW air source heat pump system): $30,000.00
- Annual cooling and heating energy required:
Maximum capacity (kW) of AC system x 80% x 10 hours per day x 365 days a year =
50 x 0.8 x 20 x 365 = 146,000kWh
- Annual water heating load met by GSHP:
As mentioned previously two hot water system are available for the kitchen. As the AC
system is rated for about half of the load, it was estimated that it would heat up one of the hot
water system only. Hence,
Average daily energy use by hot water system (kWh) x 40% (As it only operates 10 hours a
day) x 365 days =
25 (Figure 73) x 0.4 x 365 = 3,650kWh
The payback period in this situation was calculated the same way as the previous section and
using the same discount rate (8%).
4 Geothermal Air Conditioning Potential in Mining Villages
89
Table 33: 50kW GSHP system payback period estimation comparison with a current 50kW
AC system operating 10hours a day
Year No Year
Electricity
Cost
($/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
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% =
51,154kWh x 13% = 6,650.02 kWh produced from Diesel
Energy produce from diesel (kWh) x Heat rate diesel (L/hWh) x Diesel carbon
content (t(CO2)/L) =
6650.02 x 0.26 x 0.002683 = 4.6 t(CO2)
Carbon emission from Gas (Values obtained from assumptions made in REMAX):
Energy saved (kWh) x 87% =
51,154kWh x 87% = 44,504 kWh produced from Gas
x
x Gas carbon content (t(CO2)/m
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
tonnes of carbon dioxide emissions. The payback period in this case is 16 years.
4 Geothermal Air Conditioning Potential in Mining Villages
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
Figure 62: Capital cost sensitivity analysis for the 50kW system operating 10 hours a day
(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 $60,000 less). In this situation, for a 50kW system operating
10
12
14
16
18
20
22
24
-60 -40 -20 0 20 40 60
Pay
bac
k P
erio
d (
Yea
rs)
Capital cost x1000 ($)
Capital cost sensitivity analysis
4 Geothermal Air Conditioning Potential in Mining Villages
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: $185,000)
y = 0.1161x + 16.571
y = 0.0714x + 10.571
6
8
10
12
14
16
18
20
22
24
-60 -40 -20 0 20 40 60
Pay
bac
k P
erio
d (
Yea
rs)
Capital cost x1000 ($)
Capital cost sensitivity analysis
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.
5 David Goodfield’s PhD
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)
5 David Goodfield’s PhD
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
5 David Goodfield’s PhD
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.
5 David Goodfield’s PhD
97
Figure 66: MMG village‟s monitoring devices configuration
Figure 67: Side view of monitoring bores set up near MMG village
5 David Goodfield’s PhD
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)
5 David Goodfield’s PhD
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)
5 David Goodfield’s PhD
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
5
10
15
20
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
5 David Goodfield’s PhD
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)
Table 36: Monthly and annual average wind speed at 10m above ground surface at Mount
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
Figure 77: Monthly average wind speed seasonal variation at 10m above ground surface at
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
Figure 80: Frequency distribution wind speed at 50m above ground surface at Mount Magnet
(NASA, 2011)
Figure 81: Wind speed cumulative probability function at 50m above ground level at Mount
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
Figure 82: Weibull distribution factor estimation graph of wind speed 50m above ground
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
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:
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:
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:
9 Appendix
127
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:
Paul
Hardisty
Global Director of
EcoNomics
WorleyParsons
Business supervisor E:
m
Paul
Wilkinson
Matricon General and specific
information about
Mount Magnet gold
village
E:
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
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
Gaia Wind
11kW 11
120k to 170k
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
Aircon 10kW 10
130k to 170k
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
Evoco 10kW 10
100k to 150k
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
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 5 to 9 2,530.00 TL Sunny Boy, transformeless
3 10+ 2,420.00 TL Sunny Boy, transformeless
4 1 to 3 3,080.00 TL Sunny Boy, transformeless
4 4 to 11 2,915.00 TL Sunny Boy, transformeless
4 12+ 2,750.00 TL Sunny Boy, transformeless
5 1 to 3 3,575.00 TL Sunny Boy, transformeless
9 Appendix
134
5 4 to 11 3,465.00 TL Sunny Boy, transformeless
5 12+ 3,300.00 TL Sunny Boy, transformeless
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
7 5 to 9 4,259.91 Sunny Mini Central,
Transformerless
7 10+ 4,150.68 Sunny Mini Central,
Transformerless
8 1 to 4 4,525.18 Sunny Mini Central,
Transformerless
8 5 to 9 4,412.05 Sunny Mini Central,
Transformerless
8 10+ 4,298.92 Sunny Mini Central,
Transformerless
10 1 to 3 4,730.00 Sunny Mini Central,
Transformerless
10 4 to 11 4,565.00 Sunny Mini Central,
Transformerless
10 12+ 4,400.00 Sunny Mini Central,
Transformerless
10 1 to 3 5,720.00 Sunny Tripower, Transformerless,
3 phase
10 4 to 11 5,500.00 Sunny Tripower, Transformerless,
3 phase
10 12+ 5,280.00 Sunny Tripower, Transformerless,
3 phase
11 1 4,180.00 Sunny Mini Central,
Transformerless
9 Appendix
135
15 1 to 3 7,150.00 Sunny Tripower, Transformerless,
3 phase
15 4 to 11 6,875.00 Sunny Tripower, Transformerless,
3 phase
15 12+ 6,600.00 Sunny Tripower, Transformerless,
3 phase
17 1 to 3 7,700.00 Sunny Tripower, Transformerless,
3 phase
17 4 to 11 7,480.00 Sunny Tripower, Transformerless,
3 phase
17 12+ 7,260.00 Sunny Tripower, Transformerless,
3 phase
2 1 to 4 4,340.41 Sunny Island, Inverter Charger
2 5 to 9 4,232.90 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 1 to 4 5,583.35 Sunny Island, Inverter Charger
5 5 to 9 5,443.77 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
(%) $/kW Resource
Module 45% 2153.23 235W REC Solar
Inverter 9% 450 11kW SMA Sunny Mini Central transformerless
Other materials 17% 800
Installation labour 9% 450
Others (Regulatory compliance, overhead, etc) 19% 900
TOTAL ($/kW) 4753.23
Ratio
(%) $/kW Resource
Module 33% 1300 CEEG 250W Mono Panels (360deals)
Inverter 12% 450 11kW SMA Sunny Mini Central transformerless
Other materials 21% 800
Installation labour 12% 450
Others (Regulatory compliance, overhead, etc) 23% 900
TOTAL ($/kW) 3900
Ratio
(%) $/kW Resource
Module 26% 1000 XH 250W Mono Panels (360deals)
Inverter 12% 450 11kW SMA Sunny Mini Central transformerless
Other materials 21% 800
Installation labour 12% 450
Others (Regulatory compliance, overhead, etc) 23% 900
TOTAL ($/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
9 Appendix
139
9.8.5 RE POTENTIAL IN THE CURRENT POWER SYSTEM
PV + Current Power system analysis
- Project starting January 2012 with a sensitivity analysis on the project life:
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
Figure 87: NPC analysis of different PV array sizes with a project life of 7 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
Figure 88: NPC analysis of different PV array sizes with a project life of 9 years
Figure 89: NPC analysis of different PV array sizes with a project life of 12 years
$-
$500,000.00
$1,000,000.00
$1,500,000.00
$2,000,000.00
$2,500,000.00
$3,000,000.00
0 100 200 300 400
PV array (kW)
NPV ($)
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 90: NPC analysis of different PV array sizes with a project life of 15 years
Figure 91: NPC analysis of different PV array sizes with a project life of 18 years
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:
Figure 93: NPC analysis of different PV array sizes with a project life of 5 years
Figure 94: NPC analysis of different PV array sizes with a project life of 7 years
$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
Figure 95: NPC analysis of different PV array sizes with a project life of 9 years
Figure 96: NPC analysis of different PV array sizes with a project life of 12 years
$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.
Figure 97: NPC analysis of different PV array sizes with a project life of 5 years
Figure 98: NPC analysis of different PV array sizes with a project life of 7 years
$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
Figure 99: NPC analysis of different PV array sizes with a project life of 9 years
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.
Figure 100: NPC analysis of different PV array sizes with a project life of 5 years
$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
Figure 101: NPC analysis of different PV array sizes with a project life of 7 years
Figure 102: NPC analysis of different PV array sizes with a project life of 9 years
- 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
Figure 104: NPC analysis of different PV array sizes with a load factor of 3
$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
Figure 105: NPC analysis of different PV array sizes with a load factor of 6
Project life of 12 years:
Figure 106: NPC analysis of different PV array sizes with a load factor of 1
$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
Figure 107: NPC analysis of different PV array sizes with a load factor of 3
Figure 108: NPC analysis of different PV array sizes with a load factor of 6
Wind turbine + current power system analysis:
- Project starting January 2012 with a sensitivity analysis on the project life:
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.
Figure 109: NPC analysis of different wind turbine configurations with a project life of 5
years
Figure 110: NPC analysis of different wind turbine configurations with a project life of 9
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
Figure 111: NPC analysis of different wind turbine configurations with a project life of 12
years
Figure 112: NPC analysis of different wind turbine configurations with a project 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 $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
NPC (Project life: 15 years)
9 Appendix
152
Figure 113: NPC analysis of different wind turbine configurations with a project life of 18
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
NPC (Project life: 18 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 $4,500,000.00
NPV ($)
9 Appendix
153
Figure 115: NPC analysis of wind turbine configurations with a project life of 7 years
Figure 116: NPC analysis of wind turbine configurations with a project 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 $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
Figure 117: NPC analysis of wind turbine configurations with a project life of 9 years
Figure 118: NPC analysis of wind turbine configurations with a project life of 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
NPC (Project life: 9 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)
9 Appendix
155
Figure 119: NPC analysis of wind turbine configurations with a project life of 15 years
Figure 120: NPC analysis of wind turbine configurations with a project life of 18 years
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
NPC (Project life: 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 $4,000,000.00 $4,500,000.00 $5,000,000.00
NPC (Project life: 18 years)
9 Appendix
156
Figure 121: NPC analysis of wind turbine configurations with a project life of 5 years
Figure 122: 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 $4,500,000.00
NPV ($)
9 Appendix
157
Figure 123: NPC analysis of wind turbine configurations with a project life of 8 years
Figure 124: NPC analysis of wind turbine configurations with a project life of 9 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
NPC (Project life: 9 years)
9 Appendix
158
Figure 125: NPC analysis of wind turbine configurations with a project life of 12 years
Figure 126: NPC analysis of wind turbine configurations with a project 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 $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
NPC (Project life: 15 years)
9 Appendix
159
Figure 127: NPC analysis of wind turbine configurations with a project life of 18 years
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.
Figure 128: NPC analysis of wind turbine configurations 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 $3,500,000.00 $4,000,000.00 $4,500,000.00 $5,000,000.00
NPC (Project life: 18 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 $4,500,000.00
NPV ($)
9 Appendix
160
Figure 129: NPC analysis of wind turbine configurations with a project life of 7 years
Figure 130: NPC analysis of wind turbine configurations with a project 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 $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
NPC (Project life: 8 years)
9 Appendix
161
Figure 131: NPC analysis of wind turbine configurations with a project life of 9 years
Figure 132: NPC analysis of wind turbine configurations with a project life of 12 years
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
NPC (Project life: 9 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)
9 Appendix
162
Project life of 8 years:
Figure 133: NPC analysis of different wind turbine configurations with a load factor of 1
Figure 134: NPC analysis of different wind turbine configurations with a load factor of 3
$- $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
Figure 135: NPC analysis of different wind turbine configurations with a load factor of 6
Project life of 12 years:
Figure 136: NPC analysis of different wind turbine configurations with a load factor of 1
$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
Figure 137: NPC analysis of different wind turbine configurations with a load factor of 3
Figure 138: NPC analysis of different wind turbine configurations with a load factor of 6
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
Figure 139: NPC analysis of different wind turbine and PV array configuration with a project
life of 12 years
Figure 140: NPC analysis of different wind turbine and PV array configuration with a project
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
Figure 141: NPC analysis of different wind turbine and PV array configuration with a project
life of 18 years
Wind turbine + current power system analysis:
Figure 142: NPC analysis of different wind turbine and PV array configuration with a project
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
Figure 143: NPC analysis of different wind turbine and PV array configuration with a project
life of 7 years
Figure 144: NPC analysis of different wind turbine and PV array configuration with a project
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
Figure 145: NPC analysis of different wind turbine and PV array configuration with a project
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
Figure 147: NPC analysis of different system configuration with a project life of 7 years
Figure 148: NPC analysis of different system configuration with a project life of 8 years
$-
$500,000.00
$1,000,000.00
$1,500,000.00
$2,000,000.00
$2,500,000.00
$3,000,000.00
NPV ($)
$-
$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
Figure 149: NPC analysis of different system configuration with a project life of 9 years
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
Figure 151: HOMER output screen shot for project starting in January 2014
Figure 152: HOMER output screen shot for project starting in January 2016
Figure 153: HOMER output screen shot for project starting in January 2018
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.
Figure 154: HOMER output screen shot for project starting in January 2012 and an average
daily load of 8568 kWh
Figure 155: HOMER output screen shot for project starting in January 2012 and an average
daily load of 8568 kWh (Graph representation)
9 Appendix
173
Figure 156: HOMER output screen shot for project starting in January 2012 and an average
daily load of 17136 kWh
Figure 157: HOMER output screen shot for project starting in January 2012 and an average
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
measurements below 100 amps
Magnelab 0 –
200 AMP T-MAG-SCT-200 6
Sensor to undertake current
measurements below 200 amps
Magnelab 0 –
600 AMP T-MAG-SCT-600 3
Sensor to undertake current
measurements below 600 amps
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
Inside light 6 36 168.00
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
Inside light 24 36 168.00
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
Inside light 24 36 168.00
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