Method and system for identification of charging station location based on data driven optimization

This disclosure relates generally to identification of charging station location based on data driven optimization. Despite the rapid growth seen in adoption of EVs, several challenges have remained, with the major concern of choosing the location of the charging infrastructure is crucial. The state-of-art techniques to identify the location of charging infrastructure/station is based on pure optimization techniques using static number of charging stations, which may not effectively output the global optimal solution for the city as it is not performed at real-time. The disclosed technique is a flow-based solution approach that is based on daily traffic count data. The disclosed technique analyses traffic condition from vehicle count data, geography of the city or area of interest, road networks, charging station operation constraints to identify a set of candidate locations required to cover entire city or area of the interest based on a score-based ranking of each candidate location.