Risk assessment of renewable energy investments: A modified failure mode and effect analysis based on prospect theory and intuitionistic fuzzy AHP

İLBAHAR E., Kahraman C., ÇEBİ S.

ENERGY, cilt.239, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 239
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.energy.2021.121907
  • Dergi Adı: ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Risk assessment, Renewable energy, Investment risks, Fuzzy sets, Prospect theory, FEED-IN TARIFF, DECISION-MAKING, SELECTION, FRAMEWORK, DETERMINANTS, TECHNOLOGIES, GENERATION, BARRIERS, PROJECTS, CHINA
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Most countries intending to replace traditional energy sources with renewable energy sources have started to make major investments in this field. Since renewable energy is a sector requiring large amount of investment costs, evaluation of investment risks are extremely important to make the best investment decisions. However, as risk assessment is a process based on expert judgments, the indecisiveness and cognitive bias of the experts should be eliminated. Therefore, a modified Failure Mode and Effect Analysis (FMEA) based on the prospect theory and interval-valued intuitionistic fuzzy Analytic Hierarchy Process (AHP) is introduced to assess the risks in renewable energy investments for the first time. As a result of the proposed risk assessment approach, renewable energy investment risks are prioritized by effectively overcoming the indecisiveness and cognitive bias of experts. (c) 2021 Elsevier Ltd. All rights reserved.