Joint planning–control optimization of EV charging stations, battery energy storage, and DSTATCOMs in distribution networks

Abstract The increasing penetration of electric vehicles (EVs) is placing growing planning and operational demands on distribution networks due to the spatially concentrated and time-varying nature of charging loads. Although previous studies have investigated the coordinated planning of electric vehicle charging stations (EVCSs), battery energy storage systems (BESSs), and distributed static compensators (DSTATCOMs), infrastructure planning and operational control are commonly treated as separate stages, with planning decisions typically evaluated using predefined operating strategies or static operating conditions. This paper proposes an integrated planning–control optimization framework that simultaneously determines the optimal siting, sizing, and operational control of EVCSs, BESSs, and DSTATCOMs in radial distribution networks. Unlike conventional approaches, the proposed formulation embeds 24-hour BESS charging/discharging schedules and droop-controlled DSTATCOM operation directly within the planning optimization, enabling candidate solutions to be assessed under realistic time-varying operating conditions. The resulting mixed-integer nonlinear optimization problem is solved using the Harris Hawks Optimization (HHO) algorithm. Simulation studies on the IEEE 69-bus distribution system show that the proposed framework reduces the mean absolute voltage deviation by approximately 45% and decreases daily energy losses by more than 15% compared with the EV-only scenario while maintaining operational feasibility throughout the scheduling horizon. The proposed framework also exhibits limited sensitivity to the selected objective-function weighting coefficients and demonstrates competitive convergence performance relative to benchmark metaheuristic algorithms, highlighting the benefits of integrating operational control directly into the planning stage for EV-integrated distribution networks.