Comparison of Bio-Inspired Algorithms in a Case Study for Optimizing Capacitor Bank Allocation in Electrical Power Distribution

This paper investigates the Fish School Search (FSS) algorithm's effectiveness for optimizing capacitor placement in electrical distribution networks, focusing on the challenges of increasing demand and aging infrastructures. The study assesses FSS's unique capability to evade local optima, contrasting its performance with established methods like Ant Colony (AC), Constructive Heuristic Algorithm (CHA), and Genetic Algorithm (GA) in various systems, including IEEE-14, IEEE-33, and IEEE-69 buses. Results highlight FSS's superior performance in reducing active losses, using fewer resources and iterations. This research underscores the potential of bio-inspired algorithms in complex power distribution challenges and suggests new directions for algorithmic efficiency and broader application.