Cost-Effective Optimal Allocation of Electric Vehicle Charging Stations Incorporated with Distributed Generation using HMFO

The growing integration of Electric Vehicles (EVs) has posed challenges to conventional distribution networks, including higher energy demand, voltage instability, and feeder overloading. This study demonstrates that coordinated placement of Electric Vehicle Charging Stations (EVCS) with Distributed Generation (DG) units can significantly enhance network reliability and operational efficiency. To allocate the EVCS and DG with proper size and site, a Hybrid Moth-Flame Optimization (HMFO) algorithm was developed, while the Backward/Forward Sweep (BFS) method used for load flow analysis. The multi-objective optimization considered the minimization of active and reactive power losses, enhancement of the voltage profile, and price-effective operation encompassing installation, operation and maintenance (OandM), charging, and energy loss prices, addressing both the Distribution Network Operator (DNO) and Charging Station Owner (CSO) perspectives. A simulation on the IEEE 33-bus system demonstrated that HMFO outperforms Firefly and standard Moth- Flame Optimization in terms of convergence speed, price reduction, and voltage profile improvement, confirming its effectiveness for efficient, resilient, and sustainable smart distribution network planning.