Simultaneous Allocation, Sizing, and Power Factor Optimization of Wind Turbines and EV Charging Stations in Power Distribution Networks

Abstract

This study explores the application of the Runge-Kutta Algorithm (RKO), a cutting-edge metaheuristic search technique, for the simultaneous allocation, sizing, and power factor optimization of wind turbines in power distribution systems. The research also involves the concurrent allocation of three 2 MW electric vehicle (EV) charging stations, integrated alongside the wind turbine installations. The objective is to minimize power loss while ensuring the efficient integration of renewable energy sources and EV charging infrastructure. The proposed RKO-based approach is evaluated for its effectiveness in optimizing component placement and enhancing overall system performance under dynamic load conditions. Simulation results indicate that the RKO algorithm offers a robust and efficient method for reducing power loss, making it a promising tool for future energy distribution system optimization.