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Accounting for finance in electrification models for sub-Saharan Africa

Nature Energy volume 7, pages 631–641 (2022)Cite this article

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Abstract

Electrifying 600 million people in sub-Saharan Africa will require substantial investments. Integrated electrification models inform key policy decisions and electricity access investments in many countries. While current electrification models apply sophisticated geospatial methods, they often make simplistic assumptions about financing conditions. Here we establish cost of capital values, reflecting country and electrification mode (that is, grid extension, minigrids and stand-alone systems), and specific risks faced by investors and integrate them into an open source electrification model. We find that the cost of capital for off-grid electrification is much higher than currently assumed, up to 32.2%. Accounting for finance shifts approximately 240 million people from minigrids to stand-alone systems in our main scenario, suggesting a more cost-effective electrification mode mix than previously suggested. In turn, electrification models based on uniform cost of capital assumptions increase the per kWh cost of electricity by 20%, on average. Upscaling and mainstreaming off-grid finance can lower electrification cost substantially.

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Fig. 1: Cost of capital estimates for the different financing scenarios and for the different electrification modes.
Fig. 2: Results showing the newly connected populations and total investments between 2018 and 2030 based electrification mode for the defined electrification pathways and financing scenario.
Fig. 3: Map of sub-Saharan Africa comparing financing scenarios for the defined electrification pathways.
Fig. 4

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Data availability

Country-level geospatial input data for the time period (2018–2030) is from the World Bank’s Global Electrification Platform11, which is, to our knowledge, the most complete and open source data for sub-Saharan African countries. The data have also been uploaded on an online public repository72. For this analysis, we use country input files that were generated by the Global Electrification Platform that can be accessed for each country on the platform website11. The data define physical properties of individual population clusters and are required to determine the electricity consumption by households in 2030. Scenario input data can also be found in Supplementary Table 9. The maps (Fig. 3) are plotted using cluster shape file data that is also available on the World Bank’s Global Electrification Platform11. The base layers used to plot the map include water bodies73 and administrative boundaries74.

Code availability

The modified OnSSET model used for this analysis can be accessed through the GitHub public repository (https://bit.ly/3jlre4G).

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Acknowledgements

We thank interviewees and technical experts who provided valuable feedback on empirical values used in the analysis and participants at the Sustainable Energy Transitions Initiative (SETI) virtual workshop 2020, the Centre of Economic Research at ETH Zurich (CER-ETH) PhD Seminar, the Swiss Association of Energy Economics (SAEE) workshop and EPG group members who provided feedback on earlier drafts of the paper. This project has received funding from the Engineering for Development (E4D) Doctoral Scholarship Programme, which is funded by the Sawiris Foundation for Social Development and the Swiss Agency for Development and Cooperation (C.A.), and from the European Union’s Horizon 2020 research (B.S.) and innovation programme (B.S.), European Research Council (ERC) (grant agreement number 948220, project GREENFIN) (B.S.).

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Authors and Affiliations

  1. Energy and Technology Policy Group, ETH, Zurich, Switzerland

    Churchill Agutu, Florian Egli & Tobias S. Schmidt

  2. Kigali Collaborative Research Centre (KCRC), Kigali, Rwanda

    Churchill Agutu & Nathaniel J. Williams

  3. UCL Institute for Innovation and Public Purpose (IIPP), London, UK

    Florian Egli

  4. Golisano Institute for Sustainability, Rochester Institute of Technology, Rochester, NY, USA

    Nathaniel J. Williams

  5. Institute of Science, Technology and Policy, ETH, Zurich, Switzerland

    Tobias S. Schmidt & Bjarne Steffen

  6. Climate Finance and Policy Group, ETH, Zurich, Switzerland

    Bjarne Steffen

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Contributions

T.S.S., B.S. and C.A. secured project funding; C.A., T.S.S., B.S., F.E. and N.J.W. designed the research; C.A., F.E. and B.S. coordinated the data research; C.A. carried out the modelling analysis; C.A., F.E., B.S. and T.S.S. conducted interviews; and C.A., F.E., T.S.S., B.S. and N.J.W. wrote the paper.

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Correspondence to Churchill Agutu, Florian Egli, Tobias S. Schmidt or Bjarne Steffen.

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Supplementary Tables 1–9, Fig. 1 and Notes 1–3.

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Agutu, C., Egli, F., Williams, N.J. et al. Accounting for finance in electrification models for sub-Saharan Africa. Nat Energy 7, 631–641 (2022). https://doi.org/10.1038/s41560-022-01041-6

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