The use and comparison of a deterministic, a stochastic, and a hybrid multiple-criteria decision-making method for site selection of wind power plants: An application in Turkey

Abstract

Clean domestic energy is an attractive option, especially for developing countries. Wind has been one of the most appealing renewable energy sources for those as of the beginning of the 20th century. This study focuses on an important work item of the establishment phase of this important energy source: power plant site selection. Three approaches were examined based on multiple-criteria decision-making methods. Stochastic multi-criteria acceptability analysis (a simulation-based approach with different kinds of uncertain information), analytic hierarchy process (a conventional deterministic approach), and AHP-SMAA (a hybrid approach) were applied separately in Turkey. In terms of novelty, analyses were conducted both with (analytic hierarchy process) and without (stochastic multi-criteria acceptability analysis) the preference information of the decision makers. The unique hybrid method integrates stochastic multi-criteria acceptability analysis with analytic hierarchy process to allow the simulation-based experiments with deterministic variables. As a result of the approaches, the same region (Burhaniye-Pelitköy) showed up as the optimal site to establish wind power plants at every turn. The techniques are globally applicable as long as the computational data and all parameters are gathered completely.

Standardizing the factors used in wind farm site suitability models: A review

“…It can be implied that these terms describe the same siting factor, but not for certain, and this uncertainty increases if the means of data collection for each WiFSS study is different, e.g., a downloadable wind speed dataset versus expert opinion about wind speed's importance. Conversely, some studies used the same terminology to describe different siting factors; the term “Protected Areas” was used to describe forests [ 90 , 130 , 138 ], bird habitats [ 81 , 137 , 201 ], marine habitats [ 175 , 184 , 190 ], or combinations of these features. Common language for both describing and classifying siting factors is essential for any modeling discipline, such as climate modeling [ 111 ], especially given the number of recently published WiFSS studies (see Supplementary Material).…”

“…Acronyms for the listed MCDA methods: Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multicriteria Optimization and Compromise Solution (VIKOR, in Bosnian), Ordered Weighted Averaging (OWA), Best-Worst Method (BWM), ELimination Et Choice Translating REality (ELECTRE, in French), Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE), Multicriteria Interactive Decision Making (TODIM, in Portuguese). MCDA Approach Study Context Data Type (Secondary/Primary) Weighting/Ranking Method References GIS-based Onshore Secondary AHP [ [46] , [74] , [75] , [78] , [79] , [80] , [82] , [83] , [94] , [104] , [122] , [123] , [124] , [125] , [126] , [127] , [128] , [129] , [130] , [131] , [132] , [133] , [134] , [135] , [136] , [137] , [138] , [139] , [140] , [141] , [142] , [143] , [144] , [145] , [146] , [147] , [148] ] ANP [ [149] , [150] , [151] ] …”

Comparative analysis of multicriteria decision‐making approaches for evaluation hydrogen projects development from wind energy

“…Mostafaeipour et al 37 investigated the feasibility of building hydrogen plants in Afghanistan using wind turbines, and SWARA, EDAS, ARAS, TOPSIS, VIKOR techniques were used in this evaluation to rank the provinces, and Herat province was identified as a suitable place for hydrogen production. Arı and Gencer 38 located the use of wind turbines in Turkey using AHP‐SMAA methods. The Burhaniye‐Pelitköy region was chosen as the best site for energy generation.…”

A High-Resolution Wind Farms Suitability Mapping Using GIS and Fuzzy AHP Approach: A National-Level Case Study in Sudan

“…Additionally, the AHP method has been used to determine the suitable sites for wind-solar energy plants [24]. In another research, AHP has been combined with the stochastic approach (SMAA-2) to determine the best location for wind farms [25]. Another work conducted a strategy using the fuzzy set combined with AHP to identify the best locations of wind farms in Turkey based on wind speed, slope, building, and vegetation criteria [14].…”