Evaluation of sustainable energy planning scenarios with a new approach based on FCM, WASPAS and impact effort matrix

İLBAHAR E., Kahraman C., ÇEBİ S.

Environment, Development and Sustainability, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1007/s10668-022-02560-8
  • Journal Name: Environment, Development and Sustainability
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, PASCAL, ABI/INFORM, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Business Source Elite, Business Source Premier, CAB Abstracts, Geobase, Greenfile, Index Islamicus, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Fuzzy cognitive mapping, Scenario analysis, Energy capacity investments, Energy planning, FUZZY COGNITIVE MAP, DECISION-MAKING, CAPACITY EXPANSION, INTEGRATED FCM, GENERATION, SYSTEMS, MODEL, PLANT, IRAN, CONSTRUCTION
  • Istanbul Technical University Affiliated: Yes


© 2022, The Author(s), under exclusive licence to Springer Nature B.V.Energy system investments and policies have a significant role in maintaining sustainable development. The ability to forecast energy demands, energy obtained from renewable resources and their impacts on the environment and society is extremely important for an effective energy planning and policy making. However, it is a complicated issue requiring many factors, which are rarely independent and often not well defined in real-world problems, to be considered. Moreover, this planning process may require the evaluation of uncertain scenarios arising from different economic, regulatory, technological and environmental advancements. Therefore, in this study, an approach consisting of fuzzy cognitive mapping (FCM), weighted aggregated sum product assessment (WASPAS) and impact effort assessment is introduced to enable experts to rank different sustainability scenarios based on their impact and the effort needed. By using this approach, the scenarios with less effort and relatively high impact are identified for an effective energy planning.