With the rapid adoption of electric vehicles (EVs)

the inadequate deployment of urban charging infrastructure has intensified the mismatch between charging demand and power supply capacity. This paper proposes a multi-objective joint optimization planning method for electric vehicle charging stations (EVCSs) and electric vehicle swapping stations (EVSSs). First

a dynamic path optimization method based on real road network topology is presented. Then

considering EV travel characteristics and power consumption models

a spatial-temporal charging demand forecasting model is proposed. Furthermore

electric-traffic coupling principles are integrated into the planning framework to meet the refined requirements of power grid and road network coupling. Finally

the proposed approach is validated using the road network of a city in southern China

which is divided into multiple subregions based on points of interest

together with the IEEE 118-bus test system. The forecasting results reveal a bimodal temporal pattern of charging demand

with peak loads concentrated in public

workplace

and commercial areas during the daytime and shifting predominantly to residential areas at night. The planning result shows that 8 EVCS and 5 EVSS should be deployed within the study area.