Smart renewable electricity portfolios in West Africa

Abstract

The worldwide growth of variable renewable power sources necessitates power system flexibility to safeguard the reliability of electricity supply. Yet today, flexibility is mostly delivered by fossil fuel power plants. Hydropower can be a renewable alternative source of flexibility, but only if operated according to adequate strategies considering hourly-to-decadal and local-to-regional energy and water needs. Here, we present a new model to investigate hydro–solar–wind complementarities across these scales. We demonstrate that smart management of present and future hydropower plants in West Africa can support substantial grid integration of solar and wind power, limiting natural gas consumption while avoiding ecologically harmful hydropower overexploitation. We show that pooling regional resources and planning transmission grid expansion according to spatiotemporal hydro–solar–wind synergies are crucial for optimally exploiting West Africa’s renewable potential. By 2030, renewable electricity in such a regional power pool, with solar and wind contributing about 50%, could be at least 10% cheaper than electricity from natural gas.

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Fig. 1: West African countries’ power mix and targeted RE generation.
Fig. 2: Example of optimized hydro–solar–wind operation and hydropower rule curves.
Fig. 3: Locations of modelled hydro, solar and wind power plants.
Fig. 4: Total load-following potential and hydro–solar–wind mix.
Fig. 5: Contributions by country and RE resource in the power pool scenario.
Fig. 6: Illustration of how the necessary prioritizations of RE sources in West Africa differ from those implied by current policy plans.

Data availability

The ERA5 reanalysis data were downloaded from the Climate Data Store at https://cds.climate.copernicus.eu/. The data from CORDEX-Africa framework are available at http://cordex.org/data-access/esgf. EWEMBI forcing data can be accessed at https://doi.org/10.5880/pik.2019.004. Shapefiles for rivers and climate zones, used in Fig. 3, are available in the ECOWREX database60 at http://www.ecowrex.org/mapView/. Country border shapefiles, used in Figs. 3 and 6, are available in the GADM database73 at https://gadm.org/maps.html. The maps in Figs. 3 and 6 were created using QGIS74, which can be downloaded from http://qgis.osgeo.org/. Grid load data from Ghana are available at http://ghanagrid.com/index.php/loadprofile. Grid load data from Burkina Faso are available upon request, as are the data on the LCOE of existing and future hydropower plants in West Africa. LCOE data for solar and wind power in West Africa are available in the IRENA report referenced in Supplementary Note 9.4. The SWAT+ simulation results are available from Zenodo75. All other plant-level data used in the simulations are available and fully referenced in the WARPD database, provided as Supplementary Data to this paper. The data points behind the data plotted in the Figures can be found in Figshare76.

Code availability

The REVUB model code (version 0.1.0) is available at https://github.com/VUB-HYDR/REVUB under the MIT license, for Python as well as MATLAB. Datasets to run a minimal working example are available in the same repository.

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Acknowledgements

This work was performed under the project CIREG (Climate Information for Integrated Renewable Electricity Generation in West Africa), which is part of ERA4CS, an ERA-NET Co-fund action initiated by JPI Climate, funded by BMBF (DE), FORMAS (SE), BELSPO (BE) and IFD (DK) with co-funding from the European Union’s Horizon2020 Framework Program (Grant 690462). The study further benefited from financial support by the EU Horizon2020 Marie-Curie Fellowship Program (H2020-MSCA-IF-2018, proposal number 838667 – INTERACTION). We thank A. Miketa (IRENA), G. Dekelver and J. Dubois (Tractebel Engie), C. Nicolas and P. Lorillou (World Bank), S. d’Haen (formerly at Climate Analytics), A. Adebiyi (ECREEE), G. Falchetta (Fondazione Eni Enrico Mattei), P. Donk (N.V. Energiebedrijven Suriname), J. Jurasz (Mälardalen University), M. Howells (KTH), S. Far (formerly at the University of Bonn), G. Vulturius, R. Masumbuko, M. Ogeya and D. de Condappa (SEI), S. Liersch and H. Koch (PIK), S. Salack and S. Sanfo (WASCAL), and M. A. D. Larsen and L. Svenningsen (DTU) for their comments and suggestions. We acknowledge the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing the ERA5 reanalysis. In addition, we thank the World Climate Research Programme (WRCP) for initiating and coordinating the CORDEX-Africa initiative and to the modelling centres for making their downscaling results publicly available through ESGF.

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Contributions

S.S. and W.T. designed the study. S.S. developed the REVUB model, set up the WARPD database, performed the simulations and analysed the data. I.V. generated the climate change scenarios. C.J.C. and A.v.G. developed the SWAT+ simulations. D.R. provided the LCOE data. S.S. wrote the paper and designed the figures with contributions from I.V., C.J.C., D.R., R.J.B., A.v.G., N.P.M.v.L. and W.T. All authors proofread and commented on the manuscript.

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Correspondence to Sebastian Sterl.

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Supplementary information

Supplementary Information

Supplementary Notes 1−10, Figs. 1−14 and Tables 1−8.

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Supplementary Data 1

The WARPD database referenced in the text (see Methods).

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Sterl, S., Vanderkelen, I., Chawanda, C.J. et al. Smart renewable electricity portfolios in West Africa. Nat Sustain (2020). https://doi.org/10.1038/s41893-020-0539-0

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