The optimal selection of electrochemical energy storage using Bayesian BWM and TOPSIS method

Abstract

Renewable energy has developed rapidly in recent years. For tackling the issues of intermittency, volatility and uncertainty of renewable energy, the electrochemical energy storage is attracting more and more attentions. How to select the optimal one among electrochemical energy storage technologies is an important topic. In this paper, a new hybrid model is proposed for the selection of the optimal electrochemical energy storage, which the Bayesian BWM is used to determine the criteria weights and the TOPSIS method is employed to rank the comprehensive performance of different electrochemical energy storage technologies. Meanwhile, eight criteria from economic, social, environmental and technological pillars are selected. Taking four kinds of electrochemical energy storage technologies as examples, the empirical result shows the Li-ion battery should be selected as the optimal electrochemical energy storage technology for renewable energy-based power generation stations compared with lead-acid battery, Nas battery and NiMH battery. The proposed method for the optimal selection of electrochemical energy storage is valid and practical, which can provide effective reference for decision-makers.