Enhanced PSO Algorithm for Reactive Power Compensation

This document presents an enhanced PSO (Particle Swarm Optimization) algorithm specifically developed for reactive power compensation applications. The algorithm combines traditional PSO techniques with reactive power compensation strategies to optimize power system performance. Key improvements include adaptive inertia weight adjustment and dynamic social learning factors that enable more efficient convergence towards optimal capacitor bank configurations. The implementation utilizes MATLAB-based optimization functions to calculate optimal reactive power injection points, thereby improving system power factor and voltage stability. The algorithm's fitness function evaluates both technical constraints and economic factors, ensuring practical implementation viability. Through systematic parameter tuning and swarm intelligence mechanisms, this approach enhances power system stability and operational efficiency while maintaining voltage quality standards. Code implementation features modular design with separate functions for particle initialization, velocity updating, and constraint handling, making it suitable for integration with existing power system simulation platforms.