Chapter 2
Ample Renewable Energy Resources
South Africa’s location, geography and size all play a role in providing it with multiple renewable
energy resources. A coastline of around 3,000km that goes around the tip of Africa, starting from the
desert on the west coast and ending in Mozambique’s warm tropical climate, provides favourable
conditions for wind power. Most of the country is classified as semi-arid, meaning there are large
expanses of flat terrain with high irradiation making it ideal for solar power. The east coast is tropical
with large wood and sugar plantations creating biomass opportunities. Although a water scarce
country, opportunities for hydropower do exist.
Support from international agencies as well as Government have provided the technical studies and
empirical evidence required by policy makers, developers and financiers. There is certainty the sun
will shine, the wind will blow, the water will flow and the biomass stock will be reliable in sufficient
quantities to make projects viable.
The collaboration of the preceding decade between Government, industry and international partners,
has given rise to renewable energy roadmaps or resource maps, providing collated datasets and clear
guidance for resource and technology development in the country.
Wind Atlas for South Africa (WASA)
South Africa is among the countries participating in the Global Wind and Solar Atlas led by the
International Renewable Energy Agency (IRENA). The WASA project is an initiative of the South African
government, DOE, and is co-funded by the Global Environment Facility (R 8 million) with United
Nations Development Programme support, through the South African Wind Energy Programme
(SAWEP), and the Danish government (DKK 9.9 million). The development of the wind atlas was
achieved as a capacity development and research collaboration between several institutions, each
contributing specialized skills and knowledge to the project team:
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SANEDI (South African National Energy Development Institute), which is responsible for
management, coordination, contracting;
UCT CSAG (Climate System Analysis Group, University of Cape Town) in mesoscale
modelling;
CSIR (Council for Scientific and Industrial Research) for measurements, microscale modelling
and application;
SAWS (South African Weather Service) for extreme wind assessment; and
DTU Wind Energy (Dept of Wind Energy, Technical University of Denmark), partner in all
activities.
The key deliverables of WASA Phase 1 which was initiated in June 2009 and concluded in April 2014,
covering Western Cape and parts of the Northern Cape and Eastern Cape provinces, are:

10 High quality wind measurement masts and data collection operational since 2010. The wind
measurement data is used to verify the Numerical Wind Atlas (see Table 1).

The Weather Research Forecasting (WRF) model customised for wind resource modelling with wind
time series data available from 1 Sept 1990 to 31 Dec 2012. The wind time series data are particular
useful for:
•
•
•
•
Study the annual, seasonal and diurnal variations in wind resources
As input to power system modelling
Study the geographical cross correlation of wind across South Africa
Used for long-term correction of the wind resources given by the WRF wind climate files
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WRF based Verified Numerical Wind Atlas (NWA) (see figure 1) and database, including seasonal
variations for planning and development of wind farms and off-grid electrification. The level of
accuracy and granularity of the data has proven invaluable for wind power development, addressing
the problem of earlier wind atlases with low resolution and or unverified data. In particular it saves
time and costs as the bankability of a potential wind farm site can now be estimated and physical
wind measurements only to be undertaken for bankable wind sites.
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Large Scale High Resolution (250 m grid spacing) Wind Resource map (see Figure 2). The wind
resource map is an application of the Verified Numerical Wind Atlas with topography and terrain
obstacles incorporated and depicts the local wind climate that a wind turbine would encounter.
It also offers important benefits for developers, policy makers, utilities and the industry, including
the following:
 Levels the playing field between small and large industry players to identify and develop
wind hot spots.
 Assists Government in estimating the real wind resource potential.
 Identifies possible wind development zones in line with strategic environmental assessment
(SEA) studies (e.g. https://redzs.csir.co.za) or frameworks
 Long-term grid planning to connect with wind development areas.
 Wind farm planning in positioning (micro siting) the wind turbines for optimal wind
exposures.
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Map and database of extreme wind climate of the modelled areas in the three provinces (see
Figure 3)
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Information workshops, seminar and presentations at Windaba etc
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The CSIR and UCT (CSAG) respectively capacitated in micro scale and meso scale wind resource
modelling
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Training tools, software, guides, data bases
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Research publications of the results incl. final book and web presence:
 http://www.wasa.csir.co.za (online graphs)
 http://wasadata.csir.co.za/wasa1/WASAData (final reports, maps, guides and data (register
for free and log in)
 http://www.wasaproject.info/ (WASA project information, presentations, etc)
 http://veaonline.risoe.dk/wasa (WRF model which forecasts wind speed, power density and
direction of the wind over South Africa)
WASA expansion
The Danish Government in March 2013 approved further support (DKK 12 million) in expanding WASA
to cover the remaining areas of the Eastern Cape, KwaZulu-Natal and Free State provinces. Through
WASA 2 an additional five wind measurements masts are being installed with operation to commence
by Set/Oct 2015.
The GEF approved SAWEP Phase 2 in May 2015. SAWEP Phase 2 include support in the expansion of
WASA 2 to cover the remaining areas of the Northern Cape province with implementation to start in
2016.
WASA
Umean @ 61.9 m
1 YEAR
Umean @ 61.9 m
3 YEARS*
U
Data recovery
[m/s]
[m/s]
[%]
[%]
WM01
5.86
6.06
3.3
100
WM02
6.21
6.14
-1.1
93.4
WM03
7.09
7.14
0.7
100
WM04
6.59
6.71
0.9
100
WM05
8.64
8.56
-0.8
98.6
WM06
7.02
7.36
4.6
99.9
WM07
6.85
6.93
1.2
97.0
WM08
7.36
7.34
-0.3
100
WM09*
7.58
8.22
7.8
99.7
WM10*
6.55
6.55
0.0
98.8
Umean mean wind speed
* 2-year periods for WM09 and WM10:
WM09: 2010-10 to 2013-09 minus the year 2011.
WM10: 2011-03 to 2012-02 plus 2012-10 to 2013-09.
Table 1 Percentage difference in mean wind speed for WASA sites for the 1st
and after 3 years measurement
Figure 1 Verified Numerical Wind Atlas (VNWA) based on WRF, launched in April 2014
(generalized wind climate – flat terrain, 3km x 3km grid)
Figure 2 Large Scale High Resolution Wind Resource map launched in April
2014 (local wind climate, 250 m grid spacing) with the mean wind speed
(mean wind speed power density, terrain surface elevation and terrain
ruggedness also available online)
Figure 3 Extreme Wind Atlas 1:50 years 10 minute wind speed (m/s) at 10 m AGL
(standard conditions)