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A machine-learning approach to predicting Africa’s electricity mix based on planned power plants and their chances of success

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  • Galina Alova

    (University of Oxford)

  • Philipp A. Trotter

    (University of Oxford
    RWTH Aachen University)

  • Alex Money

    (University of Oxford)

Abstract

Energy scenarios, relying on wide-ranging assumptions about the future, do not always adequately reflect the lock-in risks caused by planned power-generation projects and the uncertainty around their chances of realization. In this study we built a machine-learning model that demonstrates high accuracy in predicting power-generation project failure and success using the largest dataset on historic and planned power plants available for Africa, combined with country-level characteristics. We found that the most relevant factors for successful commissioning of past projects are at plant level: capacity, fuel, ownership and connection type. We applied the trained model to predict the realization of the current project pipeline. Contrary to rapid transition scenarios, our results show that the share of non-hydro renewables in electricity generation is likely to remain below 10% in 2030, despite total generation more than doubling. These findings point to high carbon lock-in risks for Africa, unless a rapid decarbonization shock occurs leading to large-scale cancellation of the fossil fuel plants currently in the pipeline.

Suggested Citation

  • Galina Alova & Philipp A. Trotter & Alex Money, 2021. "A machine-learning approach to predicting Africa’s electricity mix based on planned power plants and their chances of success," Nature Energy, Nature, vol. 6(2), pages 158-166, February.
    • Handle: RePEc:nat:natene:v:6:y:2021:i:2:d:10.1038_s41560-020-00755-9
    DOI: 10.1038/s41560-020-00755-9
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    Citations

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    Cited by:

    1. Trotter, Philipp A., 2022. "The slow transition to solar, wind and other non-hydro renewables in Africa – Responding to and building on a critique by Kincer, Moss and Thurber (2021)," World Development Perspectives, Elsevier, vol. 25(C).
    2. Akbas, Beste & Kocaman, Ayse Selin & Nock, Destenie & Trotter, Philipp A., 2022. "Rural electrification: An overview of optimization methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    3. Parzen, Maximilian & Abdel-Khalek, Hazem & Fedotova, Ekaterina & Mahmood, Matin & Frysztacki, Martha Maria & Hampp, Johannes & Franken, Lukas & Schumm, Leon & Neumann, Fabian & Poli, Davide & Kiprakis, 2023. "PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa," Applied Energy, Elsevier, vol. 341(C).
    4. Trotter, Philipp A. & Brophy, Aoife, 2022. "Policy mixes for business model innovation: The case of off-grid energy for sustainable development in sub-Saharan Africa," Research Policy, Elsevier, vol. 51(6).
    5. Akinyemi, Taiwo & Jung, Suhyun, 2023. "Power Plants and Child Mortality in Nigeria," 2023 Annual Meeting, July 23-25, Washington D.C. 335962, Agricultural and Applied Economics Association.
    6. Nchofoung, Tii N. & Asongu, Simplice A., 2022. "Effects of infrastructures on environmental quality contingent on trade openness and governance dynamics in Africa," Renewable Energy, Elsevier, vol. 189(C), pages 152-163.
    7. Ortega-Arriaga, P. & Babacan, O. & Nelson, J. & Gambhir, A., 2021. "Grid versus off-grid electricity access options: A review on the economic and environmental impacts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    8. Mohammed Basheer & Victor Nechifor & Alvaro Calzadilla & Claudia Ringler & David Hulme & Julien J. Harou, 2022. "Balancing national economic policy outcomes for sustainable development," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    9. Müller, Leander A. & Leonard, Alycia & Trotter, Philipp A. & Hirmer, Stephanie, 2023. "Green hydrogen production and use in low- and middle-income countries: A least-cost geospatial modelling approach applied to Kenya," Applied Energy, Elsevier, vol. 343(C).
    10. Darren McCauley & Rebecca Grant & Evance Mwathunga, 2022. "Achieving energy justice in Malawi: from key challenges to policy recommendations," Climatic Change, Springer, vol. 170(3), pages 1-22, February.
    11. Kincer, Jacob & Moss, Todd & Thurber, Mark, 2022. "A coal renaissance is not coming to Africa," World Development Perspectives, Elsevier, vol. 25(C).
    12. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
    13. Karbassi, Veis & Trotter, Philipp A. & Walther, Grit, 2023. "Diversifying the African energy system: Economic versus equitable allocation of renewable electricity and e-fuel production," Applied Energy, Elsevier, vol. 350(C).
    14. Moraga, J. & Duzgun, H.S. & Cavur, M. & Soydan, H., 2022. "The Geothermal Artificial Intelligence for geothermal exploration," Renewable Energy, Elsevier, vol. 192(C), pages 134-149.

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