With China’s rapid economic development, environmental pollution and energy security issues are becoming more and more prominent, and electric vehicles, as a kind of low-pollution, renewable energy-driven transportation, have become an important alternative to traditional fuel vehicles. However, the popularization of electric vehicles faces the problem of insufficient charging infrastructure. Reasonable charging station siting not only reduces the construction cost, but also enhances the user’s charging experience. This study proposes an optimization method for electric vehicle charging station siting based on the forbidden search algorithm. By constructing a multi-objective optimization model, factors such as construction cost, user satisfaction, carbon emission and charging station service capability are considered, and the hybrid genetic taboo search (GATS) algorithm is used to solve the problem. The results show that the GATS algorithm exhibits high accuracy and fast convergence speed in the optimization process. In the test of the IEEE 30-node system, the optimized siting scheme using this method reduces the line network loss by about 15% compared to the traditional method, and the construction cost is reduced by about 10%. In addition, the siting scheme considering V2G mode further reduces the grid losses and carbon emissions. Overall, the proposed method can effectively balance the cost, carbon emission and user demand, and provides a feasible optimization scheme for the layout of EV charging infrastructure.