Solar Energy Power Plant Investment Selection with Unbalanced Hesitant Fuzzy Linguistic MULTIMOORA Method Based Score-HeDLiSF

ÇOBAN V., Onar S. Ç.

International Conference on Intelligent and Fuzzy Systems, INFUS 2020, İstanbul, Türkiye, 21 - 23 Temmuz 2020, cilt.1197 AISC, ss.274-281 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1197 AISC
  • Doi Numarası: 10.1007/978-3-030-51156-2_33
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.274-281
  • Anahtar Kelimeler: HFLTS, MULTIMOORA, Score-HeDLiSF, Solar power plant
  • Bilecik Şeyh Edebali Üniversitesi Adresli: Evet

Özet

© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.Solar energy is the most important alternative and renewable energy source in meeting the increasing energy demand. Despite technological advances, solar energy systems have a high initial cost. Therefore, the installation of solar energy systems in the right place is of great importance for the return of high investment costs. The Hesitant Fuzzy Linguistic Term Set (HFLTS) is an important tool in integrating experts’ complex linguistic knowledge into decision-making process. In this study, the psychological orientations of the specialists are taken into consideration by using unbalanced HFLTS based on the score function of hesitant fuzzy linguistic term set based on hesitant degrees and linguistic scale functions (Score-HeDLiSF) method. Unbalanced HFLTSs based Score-HeDLiSF is used in the Multi-Objective Optimization on the basis of a Ratio Analysis plus the full MULTIplicative form (MULTIMOORA) method developed by ORESTE method and alternative solar plants are evaluated.