Assessment of renewable energy alternatives with pythagorean fuzzy WASPAS method: A case study of Turkey

Esra Ilbahar*, Selcuk Cebi, Cengiz Kahraman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Citations (Scopus)

Abstract

Effective exploitation of renewable energy sources is a fundamental part of sustainable development strategies of countries. A comprehensive assessment of renewable energy sources is required to ensure maximum utilization of resources. The assessment of renewable energy alternatives is a complex problem since many criteria, even some of them are conflicting, must to be simultaneously taken into consideration. Pythagorean fuzzy sets are able to better represent uncertainty and impreciseness in an evaluation process by providing a larger domain for decision makers to express their opinions. Therefore, this study aims at assessing alternative renewable energy sources by using interval-valued Pythagorean fuzzy WASPAS method. The obtained results are compared to the results of interval-valued intuitionistic WASPAS and crisp WASPAS methods. It is concluded that bioenergy is the best renewable energy alternative for Turkey.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
EditorsCengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
PublisherSpringer Verlag
Pages888-895
Number of pages8
ISBN (Print)9783030237554
DOIs
Publication statusPublished - 2020
EventInternational Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey
Duration: 23 Jul 201925 Jul 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1029
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceInternational Conference on Intelligent and Fuzzy Systems, INFUS 2019
Country/TerritoryTurkey
CityIstanbul
Period23/07/1925/07/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

  • Pythagorean fuzzy sets
  • Renewable energy assessment
  • WASPAS

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