Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China

Under the global implementation of low-carbon economy, the development of renewable energy becomes an important way of energy saving and emission reduction. Multi-criteria decision-making (MCDM) techniques are gaining popularity in renewable power sources (RPS) evaluation since this process involves many conflicting criteria. Classical MCDM techniques assume that decisions are conducted in a deterministic environment and decision-makers (DMs) are completely rational while facing with investment risks. However, these hypotheses are not supported in the RPS selection. Fortunately, fuzzy set theory enables to cope with vagueness of evaluations in decision-making process, and cumulative prospect theory can reflect the risk preference of DMs and describe the actual behavior of them. Therefore, in this paper, a fuzzy MCDM technique based on cumulative prospect theory is proposed for selecting the most appropriate RPS in China. A case study in China is carried out to illustrate the rationality and feasibility of the proposed method. The results show that the solar PV is determined to be the best one in China, but the optimal alternative is sensitive to the prospect parameters. This research provides insightful information for the public investors with different risk preferences to evaluate the RPS and select the most appropriate one under uncertain environment.