Optimization of PV, Capacitor Bank, and EV Charging Station Allocation in a 33-Bus Power Distribution System Using the Slime Mould Algorithm

Abstract

This study presents a comprehensive approach to the optimal allocation and sizing of photovoltaic (PV) systems and capacitor banks in a 33-bus power distribution system, focusing on enhancing system performance. Simultaneously, the allocation of PV systems, capacitor banks, and electric vehicle (EV) charging stations is addressed to optimize system efficiency. The primary objectives include minimizing active power losses and improving the voltage profile across the network. To solve this complex optimization problem, the Slime Mould Algorithm (SMA), a cutting-edge metaheuristic technique, is employed as an advanced tool for distributed generation (DG) allocation. SMA's robust search capability and adaptability make it well-suited for addressing the multi-objective nature of this study, delivering optimized results that balance system losses and voltage stability. The proposed method demonstrates significant potential for improving the efficiency and stability of modern power distribution networks.