Abstract
In this study, a fuzzy multi-criteria decision-making (MCDM) framework is established to optimize the renewable energy project (REP) portfolio(s) in an efficient way. Firstly, from the perspective of sustainability, three objectives of economic, social and environmental impacts as well as 16 subordinated criteria are identified for REP performance evaluation via literature review. Secondly, the performance of REPs on these criteria is adopted the form of interval type-2 fuzzy (IT2F) numbers to fully describe the inherent uncertainties in the REP portfolio optimization problem. Thirdly, the fuzzy weights of these criteria are obtained using interval type-2 fuzzy analytic hierarchy process (IT2F-AHP) technique. Fourthly, based on the criteria performances and criteria weights, the interval type-2 fuzzy weighted averaging (IT2FWA) operator is used to aggregate the fuzzy values of REPs in term of the three objectives. Fifthly, a zero-one programming model is formulated and the non-dominated sorting genetic algorithm-II is employed to capture an optimal-Pareto set by considering the trade-off between the three objectives. Finally, to validate the effectiveness of the proposed framework, a case study in Southeast China is conducted. Results show that the criteria greenhouse gas emission reduction owns the highest weight, and three non-dominant solutions with uniform distribution are obtained.
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