A novel multi-criteria framework for selecting optimal sites for electric vehicle charging stations from a sustainable perspective: evidence from India

In urban India air pollution is a critical environmental issue with the transportation sector being a major contributor. Transitioning to electric vehicles is one essential policy decision that can reduce emissions, thus, necessitating a robust network of public charging stations. This study proposes a facility-based Multi-Criteria Decision-Making (MCDM) analysis integrated with Geographical Information System (GIS) to address site selection issues for EV charging stations. The methodology involves three steps to determine the optimal locations for EVCs: (i) defining 12 sub-criteria and weighting them using both CRiteria Importance Through Intercriteria Correlation (CRITIC) and ENTROPY, (ii) generating a suitability map for potential EVCSLs via GIS, and (iii) ranking the performance levels of EVCSLs based on the suitability map using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) methods. The comprehensive model is illustrated in Fig. 1. A case study in Telangana, India, with existing charging stations, validates the proposed approach. Sensitivity and comparative analyses demonstrate that criteria weight changes significantly impact the solution, underscoring the importance of proper criteria identification and accurate weight assignment. Among the methods compared (TOPSIS-CRITIC, TOPSIS-Entropy, WASPAS-CRITIC, WASPAS-Entropy), TOPSIS-CRITIC outperforms others in 10 out of 13 scenarios, offering larger service areas for a given number of charging stations for the given case study. The results indicate that the proposed MCDM framework is stable, reliable, and effective for EVCS location selection incorporating a holistic criteria-based framework, supporting India's goal of full EV adoption by 2030 as per its Paris Agreement commitments.