Solar energy plant project selection with AHP decision-making method based on hesitant fuzzy linguistic evaluation


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ÇOBAN V.

Complex and Intelligent Systems, cilt.6, sa.3, ss.507-529, 2020 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 6 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s40747-020-00152-5
  • Dergi Adı: Complex and Intelligent Systems
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.507-529
  • Anahtar Kelimeler: AHP, Decision making, Hesitant fuzzy linguistic terms, Solar energy
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

© 2020, The Author(s).Increased energy demand is expected to be met by reliable and continuous energy sources. Renewable energy which is obtained from nature and can continuously reload itself from natural sources is a new generation energy type. The sun, which is the main source of renewable energies and produces heat and electricity by direct and indirect methods, is an important renewable energy source. The installation of solar energy systems takes place under the basic technical, economic and political factors. Alternative solar energy plant projects are evaluated linguistically under the main criteria based on the knowledge and experience of the experts. Hesitant fuzzy linguistic terms are used to incorporate the uncertain and hesitant expressions into the decision-making process. The decision-making process that takes place with hesitant linguistic expressions in multiple sub-criteria is based on the AHP model. The inclusion of hesitant statements in the decision-making process with the AHP model enables more realistic choices among the alternatives. System technology (0.18), energy policy (0.15) and energy price change (0.13) appear as the most important factors in the pairwise comparison of the factors based on hesitant fuzzy linguistic evaluations. The results coincide with the need for high efficiency in solar energy systems, the importance of governmental supportive policies and the effects of price competition in the energy sector. Also, the closeness of the overall priority values of all projects (0.189, 0.23, 0.287, 0.135, 0.158) indicates that the decision makers take into account the effective factors.