Optimal DG Placement and Sizing for Multi-Objective Performance Enhancement of Radial Distribution Systems

Optimizing the allocation and sizing of distributed generators (DGs) in distribution networks is a significant challenge. The research aims to address this by using the Slime Mould Algorithm (SMA), a novel population-based optimization technique, to reduce active power losses through strategic DG integration. Additionally, the study presents a multi-objective approach that simultaneously minimizes active power losses (APL), enhances the voltage stability index (VSI), and improves the voltage profile (VP). This comprehensive optimization strategy seeks to holistically enhance the efficiency and reliability of distribution systems by effectively integrating distributed generations. The multi-objective problem is addressed using SMA in conjunction with the fuzzy decision-maker approach and the weighted sum technique. The performance of the applied method is evaluated on a 69-bus system, and the results are compared with those of different evolutionary approaches to demonstrate SMA's computational efficiency, convergence speed, and user-friendliness.