Linguistic multicriteria decision-making aid methods are explored, with different linguistic representation and computational models. These methods, been only recently used in energy-related applications, use linguistic variables in a finite and totally ordered scale. Building on these methods, the ‘RE2S’ integrated framework for renewable energy policy support, is presented and its pilot appraisal is discussed. This review claims that the presented extensions of the Linguistic Ordered Weighted Averaging and TOPSIS methods, based on the 2-tuple representation model and the Gödels transformation, can support energy policy problems, narrowing the differences between energy policy-makers thinking, reasoning, representation, and computing.
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