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Scenarios Analysis on Electric Power Planning Based on Multi-Scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035

Author

Listed:
  • Moussa Kanté

    (Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, Tianjin University, MOE, Tianjin 300350, China
    Department of Electrical Engineering, Vocational School of Soumangourou KANTÉ, University of Bamako, Bamako 63, Mali)

  • Yang Li

    (Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, Tianjin University, MOE, Tianjin 300350, China)

  • Shuai Deng

    (Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, Tianjin University, MOE, Tianjin 300350, China)

Abstract

The increase in electricity demand is caused by population density, gross domestic product growth and technological conditions. A long-term forecast study on the electricity demand could be a promising alternative to the investment planning of power systems and distribution. In this study, the main aim is to forecast and understand the long-term electricity demand of the Taoussa area for the sustainable development of the regions of northern Mali, by using the Model for Analysis of Energy Demand (MAED) from the International Atomic Energy Agency. To fill such a knowledge gap, the long-term evolution of electricity demand is calculated separately for four consumption sectors: industry, transportation, service and household from 2020 to 2035. The demand for each end-use category of electricity is driven by one or several socioeconomic and technological parameters development of the country, which are given as part of the reference scenario (RS) and two alternative scenarios (Low and High). These scenarios were developed based on four groups of coherent hypotheses concerning demographic evolution, economic development, lifestyle change and technological change. The results showed that the annual growth rate of electricity demand in Taoussa area in all scenarios is expected to increase by only 8.13% (LS), 10.31% (RS) and 12.56% (HS). According to the seasonal variations of electricity demand, dry season electricity demand was higher than the demand in cool season during the study period. Such a conclusion demonstrates that the proposed long-term method and related results could provide powerful sustainable solutions to the electricity development challenges of Africa.

Suggested Citation

  • Moussa Kanté & Yang Li & Shuai Deng, 2021. "Scenarios Analysis on Electric Power Planning Based on Multi-Scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035," Energies, MDPI, vol. 14(24), pages 1-24, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8515-:d:704733
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    Citations

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    Cited by:

    1. Roman V. Klyuev & Irbek D. Morgoev & Angelika D. Morgoeva & Oksana A. Gavrina & Nikita V. Martyushev & Egor A. Efremenkov & Qi Mengxu, 2022. "Methods of Forecasting Electric Energy Consumption: A Literature Review," Energies, MDPI, vol. 15(23), pages 1-33, November.
    2. Yujing Liu & Ruoyun Du & Dongxiao Niu, 2022. "Forecast of Coal Demand in Shanxi Province Based on GA—LSSVM under Multiple Scenarios," Energies, MDPI, vol. 15(17), pages 1-16, September.

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