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Potential impact of global warming on electricity demand in Niger

Author

Listed:
  • Abdou Latif Bonkaney

    (Université Abdou Moumouni)

  • Babatunde J. Abiodun

    (University of Cape Town)

  • Ibrah Seidou Sanda

    (AGRHYMET Regional Center)

  • Ahmed A. Balogun

    (Federal University of Technology)

Abstract

This study examines the potential impacts of climate change on electricity demand in Niger. Fourteen (14) regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) were analyzed for the study. The study evaluates the ability of the simulations to reproduce the present-day climate variables over Niger, builds a climate-electricity demand model to link the electricity demand with climate variables, and quantifies the potential impact of climate change on daily electricity demand at various global warming levels (GWLs: 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level. The climate-electricity demand model was built by combining the principal component analysis and the multiple linear regression analysis (hereafter, MLR). The residual analysis indicates that the MLR model complies with the assumptions of the regression analysis. The coefficient of determination (R2) of the MLR prediction is about 0.81, and the root mean square error (RMSE) is about 149.9 MWh day−1. The ensemble mean of the model simulations projects a future increase in electricity demand at all the GWLs, and more than 75% of the simulations agree on the projection. The study demonstrates how climate services could be used in quantifying the impacts of climate change on electricity demand, and the results would be valuable for reducing future climate risks in the energy sector.

Suggested Citation

  • Abdou Latif Bonkaney & Babatunde J. Abiodun & Ibrah Seidou Sanda & Ahmed A. Balogun, 2023. "Potential impact of global warming on electricity demand in Niger," Climatic Change, Springer, vol. 176(4), pages 1-22, April.
    • Handle: RePEc:spr:climat:v:176:y:2023:i:4:d:10.1007_s10584-023-03513-4
    DOI: 10.1007/s10584-023-03513-4
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    1. Craig, Michael T. & Cohen, Stuart & Macknick, Jordan & Draxl, Caroline & Guerra, Omar J. & Sengupta, Manajit & Haupt, Sue Ellen & Hodge, Bri-Mathias & Brancucci, Carlo, 2018. "A review of the potential impacts of climate change on bulk power system planning and operations in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 255-267.
    2. Adamou, Pr. Rabani & Ibrahim, Boubacar & Bonkaney, Abdou Latif & Seyni, Abdoul Aziz & Idrissa, Mamoudou, 2021. "Niger - Land, climate, energy, agriculture and development: A study in the Sudano-Sahel Initiative for Regional Development, Jobs, and Food Security," Working Papers 308806, University of Bonn, Center for Development Research (ZEF).
    3. Ahmed, T. & Muttaqi, K.M. & Agalgaonkar, A.P., 2012. "Climate change impacts on electricity demand in the State of New South Wales, Australia," Applied Energy, Elsevier, vol. 98(C), pages 376-383.
    4. Braun, M.R. & Altan, H. & Beck, S.B.M., 2014. "Using regression analysis to predict the future energy consumption of a supermarket in the UK," Applied Energy, Elsevier, vol. 130(C), pages 305-313.
    5. Huang, Kuo-Tsang & Hwang, Ruey-Lung, 2016. "Future trends of residential building cooling energy and passive adaptation measures to counteract climate change: The case of Taiwan," Applied Energy, Elsevier, vol. 184(C), pages 1230-1240.
    6. Babatunde J. Abiodun & Jimmy Adegoke & Abayomi A. Abatan & Chidi A. Ibe & Temitope S. Egbebiyi & Francois Engelbrecht & Izidine Pinto, 2017. "Potential impacts of climate change on extreme precipitation over four African coastal cities," Climatic Change, Springer, vol. 143(3), pages 399-413, August.
    7. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    8. Kaufmann, Robert K. & Gopal, Sucharita & Tang, Xiaojing & Raciti, Steve M. & Lyons, Paul E. & Geron, Nick & Craig, Francis, 2013. "Revisiting the weather effect on energy consumption: Implications for the impact of climate change," Energy Policy, Elsevier, vol. 62(C), pages 1377-1384.
    9. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    10. Jovanović, Saša & Savić, Slobodan & Bojić, Milorad & Djordjević, Zorica & Nikolić, Danijela, 2015. "The impact of the mean daily air temperature change on electricity consumption," Energy, Elsevier, vol. 88(C), pages 604-609.
    11. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
    12. Ang, B.W. & Wang, H. & Ma, Xiaojing, 2017. "Climatic influence on electricity consumption: The case of Singapore and Hong Kong," Energy, Elsevier, vol. 127(C), pages 534-543.
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