• Calculating the impact of each EVCS on the flow of network lines considering its random nature • Using structural decomposition as a powerful analytical method without the need for complex and time-consuming tasks • Proposing four indices to check CSs in different cases on normal and congested network lines • Optimal placement of CSs in the network based on the optimal effect on the flow of network lines considering two modes G2V & V2G Electric vehicles (EVs) have emerged as a key solution for mitigating environmental pollution and degradation. From the perspective of power system operators, the placement of electric vehicle charging stations (EVCSs) significantly affects network performance, particularly line flows. This paper presents a novel analytical framework to examine how EVCS placement influences power line loading across the network. The approach incorporates a structural decomposition of the electricity market to identify the contributions of key influencing factors. Both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) interactions are explicitly modeled, with the inherent operational uncertainties of EVCSs represented through uniform random sampling. Moreover, four performance indices are developed to quantify the impact of EVCS siting on line congestion. The effectiveness of the proposed method is validated using the IEEE 24-bus system. The results demonstrate that the method not only provides accurate assessments rapidly but also remains scalable and applicable to networks of varying sizes and configurations with multiple EVCS placements.
Nikkhah et al. (Sun,) studied this question.