A state-of-the-art review on multi-attribute renewable energy decision making

Abstract The utilization of renewable energy sources has come into prominence especially over the last two decades. In the literature, various methods have been utilized for the evaluation of renewable energy sources. In particular, multi-attribute decision making (MADM) methods have been widely used throughout the renewable energy literature for several purposes such as evaluation of energy policies, selection of the most suitable renewable energy source for electricity generation, evaluation of renewable energy sources, identification of the optimal site for a renewable energy facility, and selection of the best one among energy alternatives. In the scope of this paper, the studies employing MADM methods in renewable energy applications have been taken into consideration. The main aim of the study is to determine the reasons and factors explaining why these methods have been employed. It can be concluded that Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), ELimination Et Choix Traduisant la REalite (ELECTRE) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) have come into the forefront as the most widely employed methods in the literature. However, there are a few studies employing outranking methods, ELECTRE and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for the purpose of evaluating renewable energy investments/projects. Furthermore, in the literature, there are limited papers considering utilization of renewable energy sources such as geothermal, hydro, and waste. Finally, this study indicates that renewable energy exploitation is a quite suitable topic to use MADM methods.

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