Research on Expansion Decision-making of Charging Stations Based on AHP-Entropy Weight-TOPSIS Method

Expressway service-area charging stations exhibit obvious tidal traffic characteristics, giving rise to prominent supply-demand conflicts in charging capacity during holidays. Blind capacity expansion may result in capital waste and unbalanced resource allocation. This paper constructs an evaluation index system covering four dimensions: charging demand, operational benefit, resource condition, and user service. The analytic hierarchy process (AHP) is adopted to obtain subjective weights, and the entropy weight method is used to calculate objective weights. Game-theory-based weighting is applied to integrate the two sets of weights, and the TOPSIS model is employed to rank the expansion priority of seven candidate service-area charging stations. The results show that peak-hour utilization rate, average queuing time and single-pile utilization rate serve as core indicators determining station expansion priority. Among candidate stations, Station G achieves the highest comprehensive score while Station B ranks the lowest. The method combines engineering experts experience with actual station operation data, and can provide decision-making support for pile-adding and capacity-expansion of expressway charging facilities.