Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences

摘要

Under the context of low-carbon economy development, the utilization of renewable energy is deemed as an effective way for energy conservation and emission reduction. Considering about the intermittent and volatile characteristics of renewable energy, the selection of the optimal energy storage system (ESS) among various kinds of alternatives is of critical significance for giving impetus to the development of renewable energy. Therefore, it is essential to develop a comprehensive assessment technique for prioritizing various battery energy storage systems and selecting the optimal one. This paper proposed an integrated fuzzy-MCDM (multi-criteria decision making) model combining Fuzzy-Delphi approach, the Best-Worst method (BWM), and fuzzy-cumulative prospect theory (CPT) for the comprehensive assessment of battery energy storage systems. The comprehensive assessment index system consists of 15 sub-criteria from the perspectives of technology, economy, environment, performance, and sociality based on Fuzzy-Delphi method. The optimal weights are determined by the BWM based on experts' judgments which emphasized the importance of technology and environment impacts. Fuzzy theory is employed to convert interval values and crisp values to triangular fuzzy numbers (TFNs) to maximize the use of objective data information, and then the CPT model is utilized to prioritize the rankings of various alternatives considering risk preferences of decision makers and investors. The empirical result shows that the Li-ion battery is the priority selection for micro-grid demonstration projects, followed by NaS battery and NiMH battery. Sensitivity analysis discusses the influences of risk preferences on alternatives rankings. Results demonstrate that even if decision makers and investors have various risk preferences, considering about the technological, environmental, economic, social, and performance criteria, the Li ion battery is still the optimal, followed by NaS battery. (C) 2018 Published by Elsevier Ltd.