Multi-objective optimal planning of Rapid Charging Stations, Distributed Generators, and D-STATCOM in coupled networks considering waiting time

Road electrification by Electric Vehicles could successfully reduce the Green House Gas emissions. However, the EV demand at charging stations degrades the performance of the distribution system. Also, the determination of charging connectors without considering waiting time leads to infeasible solutions. Therefore, a two-stage strategy is proposed to optimally plan Rapid Charging Station (RCS), Distributed Generator (DG), and Distribution Static Synchronous Compensator (D-STATCOM) to address the above concerns. In Stage 1, RCS, DGs, and D-STATCOM were planned optimally by improving voltage stability index (VSI), active power loss (Ploss), voltage deviation (MVD), and EV user cost (EVUC). RCS connector count was identified in Stage 2 by reducing installation cost (BCRCS) and waiting time (Wt). Here, the M1/M2/C queue model was utilized in determining Wt, where M1 denotes arrival rate, M2 denotes service rate, and C is no of service points. The proposed approach is tested using an IEEE 33 bus RDN coupled with a transportation network. The optimization problem is solved using a novel Multi-Objective Rao Algorithm (MORA), and the solutions are validated using Non-Dominated Sorting Genetic Algorithm-II. The results show that the suggested strategy by MORA improved Ploss, MVD, and VSI by 64.8%, 62.4%, and 26.5%, respectively, while reducing both Wt and BCRCS.