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Comparative Analysis of Solar Panels with Determination of Local Significance Levels of Criteria Using the MCDM Methods Resistant to the Rank Reversal Phenomenon

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  • Aleksandra Bączkiewicz

    (Institute of Management, University of Szczecin, ul. Cukrowa 8, 71-004 Szczecin, Poland
    Doctoral School of University of Szczecin, ul. Mickiewicza 16, 70-383 Szczecin, Poland)

  • Bartłomiej Kizielewicz

    (Research Team on Intelligent Decision Support Systems, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland)

  • Andrii Shekhovtsov

    (Research Team on Intelligent Decision Support Systems, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland)

  • Mykhailo Yelmikheiev

    (Machine Learning Group, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland)

  • Volodymyr Kozlov

    (Machine Learning Group, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland)

  • Wojciech Sałabun

    (Research Team on Intelligent Decision Support Systems, Department of Artificial Intelligence and Applied Mathematics, Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, ul. Żołnierska 49, 71-210 Szczecin, Poland)

Abstract

This paper aims to present an innovative approach based on two newly developed Multi-Criteria Decision-Making (MCDM) methods: COMET combined with TOPSIS and SPOTIS, which could be the basis for a decision support system (DSS) in the problem of selecting solar panels. Solar energy is one of the most promising and environmentally friendly energy sources because of the enormous potential of directly converting available solar radiation everywhere into electricity. Furthermore, ever-lower prices for photovoltaic systems make solar electricity more competitive with power from conventional energy sources, increasing interest in solar panels among companies and households. This fact generates the need for a user-friendly, objective, fully automated DSS to support the multi-criteria selection of solar panels. Both MCDM methods chosen for this purpose are rank-reversal-free and precise. First, the objective entropy weighting method was applied for determining criteria weights. Final rankings were compared by two ranking correlation coefficients: symmetrical r w and asymmetrical W S . Then the sensitivity analysis providing local weights of alternatives for decision criteria was performed. The obtained results prove the adequacy and practical usefulness of the presented approach in solving the problem of solar panels selection.

Suggested Citation

  • Aleksandra Bączkiewicz & Bartłomiej Kizielewicz & Andrii Shekhovtsov & Mykhailo Yelmikheiev & Volodymyr Kozlov & Wojciech Sałabun, 2021. "Comparative Analysis of Solar Panels with Determination of Local Significance Levels of Criteria Using the MCDM Methods Resistant to the Rank Reversal Phenomenon," Energies, MDPI, vol. 14(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5727-:d:633503
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    2. Pedro Ponce & Citlaly Pérez & Aminah Robinson Fayek & Arturo Molina, 2022. "Solar Energy Implementation in Manufacturing Industry Using Multi-Criteria Decision-Making Fuzzy TOPSIS and S4 Framework," Energies, MDPI, vol. 15(23), pages 1-19, November.
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    5. Paweł Ziemba, 2023. "Selection of Photovoltaic Panels Based on Ranges of Criteria Weights and Balanced Assessment Criteria," Energies, MDPI, vol. 16(17), pages 1-18, September.
    6. Beriro, Darren & Nathanail, Judith & Salazar, Juan & Kingdon, Andrew & Marchant, Andrew & Richardson, Steve & Gillet, Andy & Rautenberg, Svea & Hammond, Ellis & Beardmore, John & Moore, Terry & Angus,, 2022. "A decision support system to assess the feasibility of onshore renewable energy infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Mohsen Ramezanzade & Hossein Karimi & Khalid Almutairi & Hoa Ao Xuan & Javad Saebi & Ali Mostafaeipour & Kuaanan Techato, 2021. "Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study," Sustainability, MDPI, vol. 13(22), pages 1-38, November.

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