Data for the paper « An all-Africa dataset of energy model “supply regions” for solar PV and wind power »

This dataset contains data provided alongside the paper “An all-Africa dataset of energy model “supply regions” for solar PV and wind power” by Sterl et al. (2022).

It concerns a novel representative subset of attractive sites for solar PV and onshore wind power for the entire African continent. We refer to these sites as “Model Supply Regions” (MSRs). This MSR dataset was created from an in-depth analysis of various existing datasets on resource potential, grid infrastructure, land use, topography and others (see Methods), and achieves hourly temporal resolution and kilometre-scale spatial resolution. This dataset fills an important research need by closing the gap between comprehensive datasets on African VRE potential (such as the Global Solar Atlas and Global Wind Atlas) on the one hand, and the input needed to run cost-optimisation models on the other. It also allows a detailed analysis of the trade-offs involved in exploiting excellent, but far-from-grid resources as compared to mediocre but more accessible resources, which is a crucial component of power systems planning to be elaborated for many African countries.

Five separate datasets are included:

Folder (1) provides shapefiles of each country’s overall feasible area for developing solar and wind power projects, under the restrictions/criteria mentioned above and described in Sterl et al. (2022).

Folder (2) provides the best 5% (“best” measured by expected LCOE, from lowest to highest, including grid and road extension costs; 5% measured in terms of coverage of a country’s area) of each country’s solar and wind development potential, including hourly time series for model input.

Folder (3) provides the corresponding shapefiles.

Folder (4) provides simplified/aggregated results in terms of MSR clusters (see Sterl et al. 2022 for details), alongside hourly time series based on the meteorological year 2018. The amount of clusters was chosen to be 2, 5 or 10 depending on country size.

Folder (5) provides PDF-file maps at the country level, showing resource strength and clustering outcomes by MSR (post-screening).

Explanations of the headers in any spreadsheet files are provided in the Supplementary Information of Sterl et al. (2022).

Countries/territories included in the dataset: 

Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Republic
Chad
Congo Republic
Democratic Republic of the Congo
Djibouti
Egypt
Equatorial Guinea
Eritrea
Eswatini
Ethiopia
Gabon
The Gambia
Ghana
Guinea
Guiné-Bissau
Côte d’Ivoire
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Morocco
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Togo
Tunisia
Uganda
Tanzania
Zambia<b