Binary Particle Swarm Optimization for Optimal Capacitor Placement and Sizing in Radial Distribution Feeders with Distorted Substation Voltages

In this paper, we propose a binary particle swarm optimization (BPSO)-based method for optimal capacitor configuration. This approach addresses the capacitor placement and sizing problem in distribution networks, specifically designed to handle scenarios with distorted substation voltages. Our methodology integrates traditional capacitor optimization techniques with BPSO algorithms, leveraging binary encoding to represent capacitor placement decisions (1 for installed, 0 for not installed) and continuous variables for sizing optimization. The algorithm implementation involves initializing particle positions representing potential solutions, updating velocities using cognitive and social components, and applying sigmoid transformation for binary position updates. Experimental validation demonstrates that our hybrid approach effectively solves capacitor configuration problems while maintaining computational efficiency through parallel evaluation of candidate solutions and adaptive parameter tuning. The results confirm significant improvement in voltage profile optimization with reduced power losses compared to conventional methods.