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

This article presents a Binary Particle Swarm Optimization (BPSO) method for optimizing capacitor bank placement and sizing in radial distribution feeders with distorted substation voltages. The algorithm automatically determines optimal capacitor locations and ratings based on substation voltage distortion characteristics to achieve improved power factor correction in distribution networks. Power factor correction is crucial for reducing energy losses and enhancing energy efficiency, making this algorithm highly valuable for power system applications. The BPSO implementation uses binary encoding where each particle's position represents potential capacitor placements (1 for installed, 0 for not installed) and sizing options. The fitness function evaluates solutions based on power loss reduction, voltage profile improvement, and harmonic distortion constraints. Key algorithm components include velocity updates using sigmoid transformation for binary positions and constraint handling for practical distribution system limits. Through this article, readers will understand the algorithm's implementation methodology, advantages in handling nonlinear optimization with discrete variables, and its practical effectiveness in real-world power system applications.