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Sustainability Assessment of Electricity Generation in Niger Using a Weighted Multi-Criteria Decision Approach

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  • Ramchandra Bhandari

    (Institute for Technology and Resources Management in the Tropics and Subtropics, TH Köln, University of Applied Sciences, Betzdorfer Strasse 2, 50679 Cologne, Germany)

  • Benjamin Eduardo Arce

    (Institute for Technology and Resources Management in the Tropics and Subtropics, TH Köln, University of Applied Sciences, Betzdorfer Strasse 2, 50679 Cologne, Germany)

  • Vittorio Sessa

    (Institute for Technology and Resources Management in the Tropics and Subtropics, TH Köln, University of Applied Sciences, Betzdorfer Strasse 2, 50679 Cologne, Germany)

  • Rabani Adamou

    (Director Master Research Program Climate Change and Energy/WASCAL, Abdou Moumouni University of Niamey, Niamey BP 237/10896, Niger)

Abstract

The majority of Niger’s population faces a widespread lack of access to electricity. Although the country lies in the Sahara belt, exploitation of solar energy is so far minimal. Due to ongoing fossil fuel exploration in the country, this fuel might dominate the future electricity supply. Today, Niger imports the most of its electricity from Nigeria. There is a need to expand electricity generation and supply infrastructures in Niger. When doing so, it is important to choose a proper set of electricity generation resource/technology that fulfils sustainability criteria. Thus, the objective of this work is to analyze a methodology in order to assess different energy technologies for Niger. A multi-criteria decision approach was selected to assess the most accessible energy system for the country. For this purpose, indicators were developed and weighted for ranking electricity generation options. Altogether 40 indicators are selected under six dimensions (availability, risk, technology, economics, environment and social) to assess eight different alternatives, considering the aggregated results and corresponding scores under each dimension. A merit list of technology and resources for electricity generation presented in this work could support the stakeholders in their decision-making for further projects implementation in the country.

Suggested Citation

  • Ramchandra Bhandari & Benjamin Eduardo Arce & Vittorio Sessa & Rabani Adamou, 2021. "Sustainability Assessment of Electricity Generation in Niger Using a Weighted Multi-Criteria Decision Approach," Sustainability, MDPI, vol. 13(1), pages 1-25, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:1:p:385-:d:474564
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    2. Mateo Barrera-Zapata & Fabian Zuñiga-Cortes & Eduardo Caicedo-Bravo, 2023. "A Framework for Evaluating Renewable Energy for Decision-Making Integrating a Hybrid FAHP-TOPSIS Approach: A Case Study in Valle del Cauca, Colombia," Data, MDPI, vol. 8(9), pages 1-21, August.
    3. Aldona Kluczek & Patrycja Żegleń & Daniela Matušíková, 2021. "The Use of Prospect Theory for Energy Sustainable Industry 4.0," Energies, MDPI, vol. 14(22), pages 1-29, November.
    4. Oz Sahin & Edoardo Bertone, 2022. "Sustainable Development of Energy, Water and Environment Systems (SDEWES)," Sustainability, MDPI, vol. 14(21), pages 1-4, October.
    5. Bhandari, Ramchandra, 2022. "Green hydrogen production potential in West Africa – Case of Niger," Renewable Energy, Elsevier, vol. 196(C), pages 800-811.
    6. Leduchowicz-Municio, A. & Juanpera, M. & Domenech, B. & Ferrer-Martí, L. & Udaeta, M.E.M. & Gimenes, A.L.V., 2024. "Field-driven multi-criteria sustainability assessment of last-mile rural electrification in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    7. AL-Alimi, Dalal & AlRassas, Ayman Mutahar & Al-qaness, Mohammed A.A. & Cai, Zhihua & Aseeri, Ahmad O. & Abd Elaziz, Mohamed & Ewees, Ahmed A., 2023. "TLIA: Time-series forecasting model using long short-term memory integrated with artificial neural networks for volatile energy markets," Applied Energy, Elsevier, vol. 343(C).

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