Wind farm site selection from the perspective of sustainability: A novel satisfaction degree‐based fuzzy axiomatic design approach

Abstract

Summary As a clean and renewable energy resource, wind energy is the most mature, environmentally friendly, and most commercially developed new energy resource in the world. Therefore, it is of great importance to determine the best location of wind farms to ensure the sustainable development of wind energy. However, since wind farm site selection often involves multiple criteria, which include qualitative and quantitative criteria, there may be conflicts between these criteria, so wind farm site selection is a complex multi‐criteria decision‐making (MCDM) problem. Therefore, the objective of this study is to propose a novel integrated MCDM approach using a fuzzy analytic hierarchy process and satisfaction degree‐based fuzzy axiomatic design (AD) to determine the optimal onshore wind farm site under a hybrid decision information environment. First, based on the literature review and experts' opinion, the evaluation index system for wind farm site selection is built from a sustainable perspective, which includes geographic, technical, economic, social, and environmental criteria. Second, fuzzy analytic hierarchy process is applied to determine criteria weights. Third, the satisfaction degree‐based fuzzy AD is employed to evaluate and rank alternatives under a hybrid decision information environment. Finally, a case study is used to illustrate the reliability and advantages of the method proposed in this paper. In addition, the information content of each alternative is calculated by aggregating the evaluation matrix of experts, and the results are IC1 = 0.058, IC2 = 0.096, IC3 = 0.16, IC4 = ∞, IC5 = ∞, and IC6 = 0.226. Then the satisfaction degree of each alternative is S1 = 0.629, S2 = 0.545, S3 = 0.501, S4 = 416, S5 = 389, and S6 = 0.463. Thus, the best wind farm site is A1. Moreover, the results show that the method proposed herein is flexible and can effectively deal with the wind farm site selection problem. Although this paper chooses China as a case study, the proposed method herein is also applicable to other countries or regions.

Sustainable development goals assessment of Erzurum province with SWOT-AHP analysis

“…There is a substantially broad literature on broadening the scope of SWOT-AHP based on sustainable development, economy, industry, supply chain and selection practices in terms of economic and social sustainability (Awasthi et al, 2018 ; Bas, 2013 ; Calabrese et al, 2019 ; Centobelli et al, 2017 ; Dania et al, 2018 ; Govindan et al, 2014 , 2020a , 2020b , 2020c ; Kim & Park, 2019 ; Lenis Escobar et al, 2020 ; Mangla et al, 2018 ; Mani et al, 2014 ; Raza et al, 2018 ; Tavana et al, 2016 ). There have been numerous attempts elaborating on the AHP and SWOT connection within the scope of environmentally sustainable development such as the selection of potential areas and suitable routes in various areas according to geographic features (Coruhlu et al, 2020 ; Datta, 2020 ; De La Vega et al, 2018 ; Kumari & Pandey, 2020 ), sustainable environmental relationship and appropriate agricultural land location selection (Feng, 2020 ; Sarı & Koyuncu, 2021 ), sustainable energy and environmental impact assessment (Anser et al, 2020 ; Ervural et al, 2018 ; Solangi et al, 2019 ; Wang et al, 2020 ), natural resource sustainability (Kajanus et al, 2012 ), sustainable tourism (Asadpourian et al, 2020 ; Fabac & Zver, 2011 ; Kişi, 2019 ; Najafinasab et al, 2020 ; Navarro-Martínez et al, 2020 ; Zorlu & Yılmaz, 2020 ) and residential areas sustainability (Esmaeilzadeh et al, 2020 ; Fatourehchi & Zarghami, 2020 ; Kramar et al, 2019 ). Furthermore, environmental, economic and social sustainability studies regarding national and regional characteristics (Alipouri et al, 2020 ; Calabrese et al, 2019 ; Jayaraman et al, 2015 ; Modibbo et al, 2020 ) related to general issues of sustainable development has narrow literature.…”

“…The scholarship associated SWOT and AHP to overcome the problems in decision-making methods in AHP processes with additional applications to AHP approaches and provide choices according to the application areas, as hybrid studies are also developed. Some of these are hybrid SWOT-ANP-FANP (Arsić et al, 2017 ); A'WOT hybrid method (Kişi, 2019 ); SWOT-AHP hybrid approach (Najafinasab et al, 2020 ); SWOT and F-AHP (Kramar et al, 2019 ); AHP-Fuzzy and TOPSIS models (Alipouri et al, 2020 ); SWOT-Fuzzy AHP approach (Wang et al, 2020 ); ANP and Fuzzy-TOPSIS-SWOT (Ervural et al, 2018 ); SWOT-AHP and Fuzzy-TOPSIS (Solangi et al, 2019 ); fuzzy axiomatic design approach (Feng, 2020 ); Fuzzy-AHP-VIKOR(Awasthi et al, 2018 ); Fuzzy-AHP (Calabrese et al, 2019 ); Fuzzy-AHP and SWOT (Tavana et al, 2016 ); SWOT-Fuzzy, TOPSIS with AHP (Bas, 2013 ); AHP-ELECTRE (Borajee & Yakchali, 2011 ); SWOT-Fuzzy COPRAS (Hatefi, 2018 ); Fuzzy-AHP-TOPSIS (Ocampo, 2019 ); Fuzzy-AHP–TOPSIS(Aksu & Küçük, 2020 ); Fuzzy DEMATEL MCDA (Yıldızbaşı et al, 2020 ); and MCDA-AHP-TOPSIS-VIKOR (Kaymaz et al, 2020 ) as hybrid multi-criteria decision-making approach literature keeps developing.…”

Multiple Criteria Decision Making for the Achievement of the UN Sustainable Development Goals: A Systematic Literature Review and a Research Agenda

“…In relation to hybrid approaches combining MCDM and non-MCDM methods, five studies employed different combinations, as follows: Delphi technique, SWOT analysis, and AHP [125], fuzzy AHP and GRA [132], fuzzy AHP and fuzzy AD [143], DEMATEL and GRA [147], fuzzy AHP, fuzzy WASPAS, and Delphi technique [149].…”

“…Aligned with the MCDM taxonomy adopted in this review, eight studies employed compromise methods, namely VIKOR [131,142], COPRAS [133,144], EDAS [134,144], ISWM [134], TOPSIS [138,141,142,145]. Four utility-based methods were applied in most of the studies, as follows: AHP [129][130][131][132][133]135,136,[138][139][140][141][142][143][144][145]149,151,152], MAUT [137,146], MA and MAV [150]. Four studies used outranking methods, namely: PROMETHEE II [131,152], PROMETHEE [148,151] and ELECTRE [151].…”

“…Finally, it is important to mention that eight studies [130,132,133,136,138,142,143,149] combined fuzzy logic with MCDM methods, and two [132,147] used artificial intelligence approaches. For instance, Ocon et al [132] used Grey Relational Analysis (GRA) combined with a fuzzy-AHP approach to select hybrid energy systems for off-grid electrification in Marinduque (Philippines).…”