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A Hybrid Multi-Criteria-Decision-Making Aggregation Method and Geographic Information System for Selecting Optimal Solar Power Plants in Iran

Author

Listed:
  • Jalil Heidary Dahooie

    (Faculty of Management, University of Tehran, Jalal Al-e-Ahmad, Nasr Bridge, Tehran 14155-6311, Iran)

  • Ali Husseinzadeh Kashan

    (Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran 14115-138, Iran)

  • Zahra Shoaei Naeini

    (Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran 14115-138, Iran)

  • Amir Salar Vanaki

    (Faculty of Management, University of Tehran, Jalal Al-e-Ahmad, Nasr Bridge, Tehran 14155-6311, Iran)

  • Edmundas Kazimieras Zavadskas

    (Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

  • Zenonas Turskis

    (Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

Abstract

Policy-makers should focus on solar energy due to the increasing energy demand and adverse consequences such as global warming. Conflicting criteria influence choosing the most desirable place to construct a Solar Power Plant (SPP). Researchers have popularized multicriteria decision-making (MCDM) methods because of the potential. Although the simultaneous use of several methods increases the robustness and accuracy of the results, existing methods to integrate MCDM methods mainly consider the same weight for all methods and utilize the alternatives ranking for the final comparison. This paper presents a hybrid decision-making framework to determine the best location for SPPs in Iran using a set of criteria extracted from the literature and expert opinions. An initial list of decision-making alternatives is prepared and evaluated using GIS software in terms of criteria. Decision-makers prioritized the identified alternatives using the MCDM methods, including SWARA and different ranking methods (TOPSIS, TODIM, WASPAS, COPRAS, ARAS, and MULTIMOORA). Finally, the CCSD method aggregates the results and identifies the best location. Results highly correlate with the results of previous methods and demonstrate the robustness of the proposed approach and its capability to overcome the limitations of previous methods.

Suggested Citation

  • Jalil Heidary Dahooie & Ali Husseinzadeh Kashan & Zahra Shoaei Naeini & Amir Salar Vanaki & Edmundas Kazimieras Zavadskas & Zenonas Turskis, 2022. "A Hybrid Multi-Criteria-Decision-Making Aggregation Method and Geographic Information System for Selecting Optimal Solar Power Plants in Iran," Energies, MDPI, vol. 15(8), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2801-:d:791610
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    2. Chia-Nan Wang & Yu-Chi Chung & Fajar Dwi Wibowo & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen, 2023. "Site Selection of Solar Power Plants Using Hybrid MCDM Models: A Case Study in Indonesia," Energies, MDPI, vol. 16(10), pages 1-24, May.
    3. Luka Djordjević & Jasmina Pekez & Borivoj Novaković & Mihalj Bakator & Mića Djurdjev & Dragan Ćoćkalo & Saša Jovanović, 2023. "Increasing Energy Efficiency of Buildings in Serbia—A Case of an Urban Neighborhood," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    4. Asrin Seyedzahedi & Salah Bahramara, 2023. "Facilitating Investment in Photovoltaic Systems in Iran Considering Time-of-Use Feed-in-Tariff and Carbon Market," Energies, MDPI, vol. 16(3), pages 1-20, January.
    5. Andrius Tamošiūnas, 2023. "Selecting Rooftop Solar Photovoltaic Modules by Measuring Their Attractiveness by a Categorical-Based Evaluation Technique (MACBETH): The Case of Lithuania," Energies, MDPI, vol. 16(7), pages 1-22, March.

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