Evaluation of Renewable Energy Resources in Turkey using an integrated MCDM approach with linguistic interval fuzzy preference relations
Gülçin Büyüközkan and
Sezin Güleryüz
Energy, 2017, vol. 123, issue C, 149-163
Abstract:
The use of Renewable Energy Resources (RER) is growing rapidly for energy generation and several studies indicate that these will have a huge contribution in the future. Selecting RER is a complex problem involving different criteria and alternatives. The first aim of the study is the development of an evaluation model to select the most appropriate RER in Turkey. Evaluation of RER alternatives can be seen as a multi criteria decision making (MCDM) problem that can be solved with flexible tools to handle complex situations and assist decision makers (DMs) in mapping out the situation. In this process, Group Decision Making (GDM) involves multiple DMs who have different goals or ways of thinking and can assess the decision process distinctively different from others. Linguistic interval fuzzy preferences with DEMATEL, ANP, TOPSIS integrated techniques are utilized to eliminate uncertainty and to better represent DMs' preferences. The originality of the paper comes from its ability to propose effective and comprehensive evaluation model for both Turkey and literature and apply to a real industrial problem to improve the RER selection process. Another contribution is to adapt integrated techniques including linguistic interval fuzzy preferences with DEMATEL, ANP, TOPSIS for the first time.
Keywords: Renewable energy resources; Linguistic interval fuzzy preference relations; Group decision making; DEMATEL; ANP; TOPSIS (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544217301445
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:123:y:2017:i:c:p:149-163
DOI: 10.1016/j.energy.2017.01.137
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().