Renewable Energy Database and
the South African Wind Atlas
Colloquium on Energy Planning
Dept of Energy
29-30 March 2012
Gallagher Convention Centre
Outline
3 key Questions
Potential, Cost
Reliability
Technologies
Wind Atlas
Users
Conclusion
Recommendations
2
Questions
What is the renewable energy (practical) potential?
What is the cost of renewable energy technologies?
How reliable is renewable energy?
3
Renewable Energy
Resource (SARERD)
4
Wind Resource
Studies
DME; R. Diab 1995
SARERD, 2001
K Hagemann, University
of Cape Town (2008)
Tripod Review of Wind Energy Resources in South Africa (2002)
concluded:
These studies are inconclusive and under estimate the true wind energy
potential as weather measurement stations at 10 m were used and in may
cases these stations are shaded by buildings etc from measuring the true
wind potential; and
Recommended that a dedicated wind energy measurement programme
needs to be undertaken to confirm the true wind energy potential in SA
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Renewable Energy
Cost
6
Reliability of Wind

Impact of Wind Generation in South Africa on Capacity Planning & System Operation
Capacity Credit
Wind is a variable energy resource. It is therefore important to know what is the capacity contribution of wind energy i.e. what is
the capacity credit of wind energy which can be defined as the additional load that the system can carry when wind power is
added, maintaining the same reliability level.
Capacity Credit of Wind Generation in South Africa (GTZ, DoE, Eskom, 2011)
Scenario 1: Year 2015, 2000MW installed wind generation capacity: CC=26,8 %
Scenario 2: Year 2020, 4800MW installed wind generation capacity: CC=25,4%
Scenario 3: Year 2020, 10000MW installed wind generation capacity: CC=22,6%
As overall conclusion, it can be stated that the capacity credit of wind generation in South Africa will be between 25% and 30%
for installed wind generation of up to 10 000MW.

Impact of Wind Energy in South Africa on System Operation
The main impact on system operation will result from the limited predictability of wind speeds and not from absolute wind speed
variations.
It can further be concluded that it is very likely that it will be possible to operate the system safely, without increased dynamic
performance requirements for the conventional power plants of South Africa.
7
Renewable Energy
Technologies
No lack of commercial, viable and proven
renewable energy technologies
Localisation issues, standards, testing,
certification, “carrot and stick” balance, industry
growth and sustainability, net metering
regulations, grid code
Emerging market: decentralised, urban, rural
(min-hybrid), stand alone and integrated (e.g.
roof mounted PV, wind turbine, net metering)
renewable energy systems, smart grid
R&D opportunities: customising and integration
of renewable energy technologies for “Africa”
and similar conditions (logistics, distances, e.g.
smaller, higher efficient, robust (gearless,
permanent magnet generator), easy
transportable wind turbines, lighter, stronger
composite materials etc)
8
Wind Atlas, Why?
Wind, besides solar, makes out the biggest contribution of
the renewable energy mix with the 2nd highest cost (based
on RFP Bid ceiling price R1150/MWh)
IRP 2010 to 2030, 42%, 17.8 GW of which 20%, 8.4 GW
wind new build to come from renewable energy (8.4 GW
PV, 1 GW CSP)
Renewable Energy IPP Procurement Programme 3.725
GW of which 1.85 GW wind, 1.45 GW PV, 0.2 GW CSP
Energy in wind
P = ½ U3
[W/ m2]
GHC mitigation 30 885.51 tons CO2/MW (20 year lifetime,
0.27 capacity factor)
Water savings of 229 l/MWh (compared to coal fired
power stations)
Wind speed U
[m/s]
New industry, job creation
Wind measurements are in one point in space
Wind varies significantly across the terrain
Spatial distribution needed for planning and projects
Accuracy is essential (ΔU of 5%
ΔP of 15%)
Modelling is necessary and challenging
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Wind Atlas Method
Inputs
measured time-series of wind speed and direction –
observed wind climate (Observational Wind Atlas)
terrain topography – elevation, roughness and obstacles –
from digitised maps, SRTM data, Google Earth
Outputs
generalised regional wind climate for the specific location
Applications
energy production estimates for wind farms in the region
near the meteorological station
Wind Power Shanghai 2007
Risø National Laboratory • Technical University of Denmark
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Process
Global
Measurements
wind farm
G
Mesoscale modeling
Microscale modeling
Regional wind climate
Local wind
Global wind resources
Presentations and links to
information are available at the
SANERI web site
http://www.wasaproject.info
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Verification
10 minutes data and graphs available online on the project web site at
CSIR: http://www.wasa.csir.co.za
Data download
http://wasadata.csir.co.za/wasa1/WASAData
WASA
Data
recovery
(%)
Umean @ 61.5m
(m/s)
WM01 Alexander Bay
100.0
5.83
WM02 Calvinia
100.0
6.19
WM03 Vredendal
100.0
7.13
WM04 Vredenburg
100.0
6.68
95.8
8.58
WM06 Sutherland
100.0
7.00
WM07 Beaufort West
100.0
6.95
WM08 Humansdorp
100.0
7.36
WM09 Noupoort
89.6
7.55
WM10 Butterworth
92.4
6.52
WM05 Napier
Date must be accurate, representative >1 year
> 90% data recovery, reliable
IEC and Measnet Wind Measurement Standards
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Microscale Modeling
WM01
WM02
WM03
WM04
WM05
WM06
WM07
WM08
5.0
10.0
Wind speed at 80 m above ground level
WM09
WM10
WAsP resource grids from Observational Wind Atlas
10 x 10 km2 grid
100 meter grid spacing
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rical Wind Atlas for South Africa - Generalized climatological (30-year) annual mean wind speed [m/s] 100 m above ground level, flat terrain, 3 cm ro
Verified Numerical
Wind Atlas
Met mast
1
2
3
4
5
6
7
8
9
10
OBS Wind Climate
6.16
6.62
7.19
7.33
8.99
7.44
7.45
7.71
7.5
6.32
NUM Wind Climate
5.33
7.01
6.63
7.19
8.35
7.24
6.61
7.66
7.58
6.09
mean error
mean absolute error
Error [%]
-13.47
5.89
-7.79
-1.91
-7.12
-2.69
-11.28
-0.65
1.07
-3.64
-4.16
5.55
Uncertainties assessed
Public domain
Industry-standard
Traceable and transparent
Platform for future development
First Verified Numerical Wind Atlas for South Africa - Generalized climatological (30-year) annual mean
wind speed [m/s] 100 m above ground level, flat terrain, 3 cm roughness everywhere
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Resolution is key
Numerical Wind Atlas
•
•
•
Grid cell size 5120 m
Wind farm of five 2 MW turbines
Estimated AEP = 39 GWh
Microscale modeling
•
•
•
Grid cell size 20 m
Wind farm of five 2 MW turbines
Estimated AEP = 55 GWh
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Verified Numerical
Wind Atlas Database
The Numerical Wind Atlas Database contains the
generalised1 wind climate data sets (.lib files) for every 5
km × 5 km, corresponding to approximately 15000 data
points (“virtual masts”) that can be employed directly
with WAsP (licensed version) for wind farm planning and
wind resource assessment
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Users
Authorities
Policies, regulations, plans
Planners
Resource and development planning
Investors, owners and banks
Financial planning, risk assessment and decisions
Developers (small and large)
Project development
Industry (small and large)
Project design and implementation,
Wind turbine design and development
Power sector
Power system planning, development and operation
Consultants
Independent expertise and tools development
Academic community
Research, methods and tools development
All need the Wind Atlas, using WAsP or similar micro-scale model to calculate estimated energy production
from wind farms as part of project and planning decisions.
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1
WASA Wind Atlas
13
Extreme Wind
Climate
Information on extreme winds essential in the design of wind farms – situated in areas with relatively
strong winds
Estimations from observations
Long measuring periods and density of measurements should be adequate.
Some Results
Dominance of
strong wind
mechanisms on
gust time-scale.
1:50 year gust
quantiles from
observed data.
• Work in progress:
Use of global reanalysis data, mesoscale modeling, SAWS data, WASA data and microscale
modeling
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WRF Wind Forecasts
http://veaonline.risoe.dk/wasa/
Averaged diurnal cycle
October 2010 – WM01
October 2010
19
SA Wind Potential
Wind atlas values @ 100 m a.g.l. (z0 = 0.03 m)
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Conclusion
Several attempts have been made to quantify SA’s Renewable Energy Resource (SARERD,
SAREBC)
Solar and Wind contribute biggest share of SA’s Renewable Energy Resource base and highest cost
State of the Art Verified and Traceable Wind Atlas in place
Launched 13 March 2012
Public domain
Level playing field
Save time and money
Not a substitution for mandatory wind measurements
Application of the Verified Wind Atlas in e.g. wind farm planning, layout and resource assessment
demonstrated
Reliability of Wind Energy quantified
Commercial, viable Renewable Energy Technologies available
Opportunity for SA to leapfrog Renewable Energy (wind) R&D
Opportunity for decentralised rural/urban application of Renewable Energy technologies, lacking
policy and regulatory framework
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Recommendations
Undertake a National Audit of SA’s Renewable Energy Resources e.g. Update
SAREBC
Develop a Verified and Traceable Solar Atlas for South Africa
Expand Capacity Credit studies to other Renewables and investigate combined
Capacity Credit
Update Renewable Energy Macro-economic study (localisation, job creation,
spin offs etc)
Coordinate and direct appropriate Renewable Energy R&D
Support decentralised rural/urban renewable energy demonstration projects
and develop supporting policy, legal and regulatory framework
Support local, regional expansion and international collaboration e.g..
IRENA/CEM Global Solar and Wind Atlas
22
Acknowledgement
The Wind Atlas for South Africa (WASA) is an initiative of the Department of Energy (DoE) and the project is cofunded by UNDP/GEF through the South African Wind Energy Programme (SAWEP) and the Royal Danish
Embassy
SANERI (South African National Energy Research Institute)
executing partner – contracting the implementing partners
coordination and dissemination
UCT CSAG (Climate System Analysis Group, University of Cape Town)
mesoscale modelling
CSIR (Built Environment, Council for Scientific and Industrial Research)
Measurements, microscale modelling, application
SAWS (South African Weather Service)
extreme wind assessment
DTU Wind Energy* (Dept of Wind Energy, Technical University of Denmark)
partner in all activities
* the original DTU partner (Risø DTU) is part of DTU Wind Energy established Jan 2012
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Thank You
Andre Otto
[email protected]
+27 (0)82 877 0128
http://www.wasa.csir.co.za (online graphs, Guide)
http://wasadata.csir.co.za/wasa1/NWA_downloads.html (downloads)
WRF http://veaonline.risoe.dk/wasa
SANERI WASA http://www.wasaproject.info/