Integrated Control of DER Placement and Network Reconfiguration in EV-Charging Distribution Systems Using Multi-Optimization Techniques
Keywords:
Distributed Energy Resources, Electric Vehicle Charging Station, Grey Wolf Optimization, Particle swarm optimization, Whale optimization, L-index, Voltage Stability, Power Loss ReductionAbstract
The integration of distributed energy resources (DERs), such as photovoltaic (PV) systems, into power distribution networks is critical for enhancing grid reliability, reducing power losses, and promoting renewable energy adoption. Fast charging stations (FCSs), due to their high energy demand, further complicate grid operation, particularly in maintaining voltage stability and coordinating power supply. While previous studies often address DERs placement or control strategies in isolation, this study proposes a unified framework that optimizes both the placement and sizing of DERs in combination with advanced grid control mechanisms. The proposed approach uses a hybrid of three metaheuristic algorithms: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA). The multi-objective formulation focuses on minimizing power loss and cost, improving voltage profiles, and reducing the L-index. A notable contribution of this work is the integration of Volt/Var and power factor (PF) management into the optimization process, which enables practical grid stabilization under steady-state conditions. The methodology is applied to the IEEE 33-bus distribution network and validated through simulation. Results indicate that the hybrid method performs better than traditional single-algorithm approaches, achieving significant power loss reductions and voltage improvements. These findings provide a practical roadmap for distribution system planning under high DERs and FCS penetration.
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