IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v176y2023i4d10.1007_s10584-023-03513-4.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10584-023-03513-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10584-023-03513-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. 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.
    11. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Xian-Xiang, 2018. "Linking residential electricity consumption and outdoor climate in a tropical city," Energy, Elsevier, vol. 157(C), pages 734-743.
    2. Wang, Yaoping & Bielicki, Jeffrey M., 2018. "Acclimation and the response of hourly electricity loads to meteorological variables," Energy, Elsevier, vol. 142(C), pages 473-485.
    3. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
    4. Nnaemeka Vincent Emodi & Taha Chaiechi & ABM Rabiul Alam Beg, 2018. "The impact of climate change on electricity demand in Australia," Energy & Environment, , vol. 29(7), pages 1263-1297, November.
    5. Óscar Trull & J. Carlos García-Díaz & Alicia Troncoso, 2019. "Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter," Energies, MDPI, vol. 12(6), pages 1-16, March.
    6. Reza Fazeli & Brynhildur Davidsdottir & Jonas Hlynur Hallgrimsson, 2016. "Climate Impact On Energy Demand For Space Heating In Iceland," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-23, May.
    7. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
    8. Du, Kerui & Yu, Ying & Wei, Chu, 2020. "Climatic impact on China's residential electricity consumption: Does the income level matter?," China Economic Review, Elsevier, vol. 63(C).
    9. Li, Jianglong & Yang, Lisha & Long, Houyin, 2018. "Climatic impacts on energy consumption: Intensive and extensive margins," Energy Economics, Elsevier, vol. 71(C), pages 332-343.
    10. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Yau, Y.H. & Pean, H.L., 2011. "The climate change impact on air conditioner system and reliability in Malaysia—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4939-4949.
    12. Santágata, Daniela M. & Castesana, Paula & Rössler, Cristina E. & Gómez, Darío R., 2017. "Extreme temperature events affecting the electricity distribution system of the metropolitan area of Buenos Aires (1971–2013)," Energy Policy, Elsevier, vol. 106(C), pages 404-414.
    13. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
    14. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    15. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    16. Jaume Rosselló Nadal & Mohcine Bakhat, 2009. "A new approach to estimating tourism-induced electricity consumption," CRE Working Papers (Documents de treball del CRE) 2009/6, Centre de Recerca Econòmica (UIB ·"Sa Nostra").
    17. Jieyi Kang & David Reiner, 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers EPRG2113, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    18. Wang, Yuanyuan & Wang, Jianzhou & Zhao, Ge & Dong, Yao, 2012. "Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China," Energy Policy, Elsevier, vol. 48(C), pages 284-294.
    19. Mestekemper, Thomas & Kauermann, Göran & Smith, Michael S., 2013. "A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting," International Journal of Forecasting, Elsevier, vol. 29(1), pages 1-12.
    20. Pielow, Amy & Sioshansi, Ramteen & Roberts, Matthew C., 2012. "Modeling short-run electricity demand with long-term growth rates and consumer price elasticity in commercial and industrial sectors," Energy, Elsevier, vol. 46(1), pages 533-540.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:climat:v:176:y:2023:i:4:d:10.1007_s10584-023-03513-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.