SANEA Lecture Series South Africa's Wind Power Potential Dr Kilian Hagemann G7 Renewable Energies (Pty) Ltd Member of the South African Wind Energy Association (SAWEA) Cape Town, 13 Feb 2013
Presentation Overview Brief introduction Wind Resource of South Africa (bulk) DoE REIPPPP process for wind Costs of wind power and variability
Personal Intro Involved in wind power since 2001 Board member of SAWEA 2001/2002, member since PhD UCT Mesoscale Wind Atlas of SA in 2008 Director of G7 Renewable Energies since 2009 Vision 100% Renewables by 2050
Company Intro G7: wind farm developer with high ambitions 5 projects in pipeline (~850MW total capacity) Preparing for REIPPPP / RfP round 3 Start of construction Q3 2014 (if successful in round 3)
SAWEA Intro not-for- profit organisation representing the SA wind industry Membership base: manufacturers, suppliers, consultants, developers, private equity Primary aim: promote the sustainable use of commercial wind energy in SA Founding member of the SA Renewable Energy Council (SAREC)
Wind Resource of South Africa History of wind resource studies done: 1995 Roseanne Diab (now obsolete) 4% potential 2001 Eskom/CSIR (now obsolete) 2008 Mesoscale Wind Atlas 18km (soon obsolete) 35% potential 2012 First WASA wind map at 5km, research ongoing Every subsequent study found higher resource
Mean absolute error 17.6% (17 stations) Average 10m Wind Speed Maps Eskom/CSIR 2001 2008 Mesoscale Wind Atlas (18km)
Wind Atlas of South Africa (WASA) Project - Overview WASA project started in 2009 Project components: 10 x 60m measurement masts for 3 years WAsP/Kamm wind map at 5x5km resolution WRF mesoscale wind map at 5x5km resolution Extreme wind atlas Future expansion plans (more masts, more detailed modelling, expand coverage)
WASA Project - Institutions SA National Energy Development Institute project lead Danish Technical University (ex Risø) technical oversight University of Cape Town / CSAG WRF modelling CSIR measurement masts SA Weather services extreme wind atlas
WASA Project - Status All 10 wind masts operational since Sep 2010 (already 2 complete years of high quality data) First verified WAsP/Kamm 5x5km numerical wind atlas published in March 2012 WRF modelling (fully dynamic downscaling) ongoing, currently at 4x4km
WASA Project First wind map
WASA Project - Accuracy Met Mast Observed Wind Atlas Average (2Y) Numerical Wind Atlas (1Y, model) Relative Error WM01 6.34 m/s 5.33 m/s -15.93% WM02 6.50 m/s 7.01 m/s 7.85% WM03 7.19 m/s 6.63 m/s -7.79% WM04 7.39 m/s 7.19 m/s -2.71% WM05 9.00 m/s 8.35 m/s -7.22% WM06 7.55 m/s 7.24 m/s -4.11% WM07 7.48 m/s 6.61 m/s -11.63% WM08 7.72 m/s 7.66 m/s -0.78% WM09 7.72 m/s 7.58 m/s -1.81% WM10 6.32 m/s 6.09 m/s -3.64% Mean Absolute Error 6.35% @7.5m/s wind resource, 6.35% error in average wind speed translates into 18% error in electricity generation
International Comparison Top 5 wind markets worldwide (GWEC 2013): 1 China (75.6GW) 2 USA (60.0GW) 3 Germany (31.3GW) 4 Spain (22.8GW) 5 India (18.4GW) SA s wind resources can compete, take a qualitative look at their wind maps
South Africa Average Wind Speeds Source: www.vortex.es Resolution: 9x9km
China Average Wind Sp eeds Source: www.vortex.es
USA Average Wind Speeds Source: www.vortex.es
Germany Average Wind Speeds Source: www.vortex.es
Spain Average Wind Speeds Source: www.vortex.es
India Average Wind Speeds Source: www.vortex.es
International Comparison Quantitative for Top 10 (2010) Rank Country Installed Capacity (GW) Wind Generation (TWh) Country Wide Capacity Factor 1 United States 39.14 94.65 27.6% 2 China 31.10 44.62 16.4% 3 Germany 27.20 37.79 15.9% 4 Spain 20.70 44.17 24.4% 5 India 13.07 19.91 17.4% 6 France 5.96 9.97 19.1% 7 Italy 5.79 9.13 18.0% 8 United Kingdom 5.38 10.18 21.6% 9 Canada 3.97 9.56 27.5% 10 Denmark 3.80 7.81 23.4% Top 10 Average 21.1% Source: US EIA http://www.eia.gov/ for 2010 Round 1 REIPPPP average: 35% capacity factor (!)
Total Resource Estimation 2008 figure integrated total wind potential by considering following criteria: Proximity to roads (minimum secondary) Proximity to transmission lines (>=66kV) Minimum capacity factor (2MW Vestas V80) given hub height (60m, 80m or 100m) Density of 1 turbine per km 2 (accounts for siting issues)
Total Potential Calculation Three scenarios: Scenario Maxim um roads Maxim um transm ission Hub Height Minim um capacity dist ance dist ance fact or pessim ist ic 3km 3km 60m 35% realist ic 4km 4km 80m 30% opt im ist ic 5km 5km 100m 25% Scenario Annual Elect ricit y Generat ion Capacity pessimistic 20.0 TWh 8.7% 6 GW realistic 80.5 TWh 35.1% 26 GW 157.2 TWh optimistic 68.5% 56 GW
Total Resource vs IRP2010 IRP2010 foresees 9.1GW of wind by 2030 => comparable to 2008 conservative scenario (6GW) This will result in only sites with capacity factors of 35% and above to be realised going forward (cheapest wind) Provided competitive bidding framework remains Fundamentals right for increase in wind allocation for IRP2012(2013?)
DoE REIPPPP Overview - Wind Round 1 634 MW started construction Round 2 563 MW awarded, Financial Close due in March 2013 Round 3 19 Aug 2013 deadline, 653 MW left to be built by 2016 A further 1470MW to be on the grid by 2017-2020 So far mostly in line with IRP2010
Wind Power under REIPPPP Round 1 undersubscribed full 1850MW available too little time => no competition, just had to qualify hence most bids near R1.15/kWh Round 2 oversubscribed (~20 bids, 7 selected) Strong competition => R0.89/kWh average Price competition in round 3 will be fierce even lower tariffs possible, capacity factors likely 40-45%
Wind Power Costs? Eskom blended tariff: CFO - cost reflective @ R0.90/kWh MYPD 3 application 16% increases for 5 years Wind: R0.89/kWh, round 3 likely to be similar or even less Coal Medupi: R0.97/kWh (Nersa LCOE calculation) Coal Kusile: R1.10- R1.30/kWh (?)
Electricity Tariff in c/kwh Wind Power Costs Full Grid Parity by 2016/2017 140 Eskom vs REIPPPP Round 2 Wind Tariffs over MYPD 3 Period 130 120 110 100 90 80 April 2011 base date, 5.7% CPI after Eskom MYPD3 16% Eskom 13% (hypoth.) Gouda Waainek Chaba West Coast 1 Grassridge&Tsitsikamma Amakhala Emoyeni Wind Avg Rnd2 70 60 2011 2012 2013 2014 2015 2016 2017
Wind Power Variability? SA s Geographic Advantage many different climate zones => always windy somewhere Own 2008 research: 10% of installed base can be relied on during winter peak Eskom/GTZ 2011 research: 25-30% capacity credit attributable to dispersed wind farms relative to new coal fired power stations Most of the variability can be managed through adequate forecasting
Conclusions South Africa has an excellent wind resource, dispersed geographically Enough wind to satisfy a large chunk of our electricity needs DoE s REIPPPP provides a solid basis for wind power in SA, keeping costs down & capacity factors high Cost of wind power already competitive with NEW coal, will reach grid parity by 2016/2017
Q&A