An interval type-2 fuzzy analysis towards electric vehicle charging station allocation from a sustainable perspective

Electric vehicles (EVs), as an efficient and environmentally friendly method for reducing fossil fuel use and air pollution, are becoming more popular as governments seek to implement sustainable development. Initial concerns about the high cost and limited travel range of EVs have now been mitigated through the convenient and efficient deployment of electric vehicle charging stations (EVCSs). The State Grid Sichuan Electric Power Company intends to construct six EVCSs in Tianfu New district, which is expected to play a significant role in the sustainable development of western China. As proper siting is the foundation for EVCS construction, in this paper, a multi-criteria group decision making (MCGDM) framework with linguistic information is proposed to deal with the EVCS siting in Tianfu New district. Thirteen criteria from four influencing aspects are identified to estimate the impact of EVCS construction. To address imprecise information and vague concepts in human language, interval type-2 fuzzy numbers (IT2 FNs), which can effectively reduce information leakage, are applied to model the linguistic terms. The entropy weight method and a rough consensus reaching process are introduced to ensure the rationality of final decision. The results show that the proposed MCGDM is feasible and efficient for EVCS site selection.