Solving Power System Optimization Problems Using Standard PSO Algorithm

This document presents the implementation of standard Particle Swarm Optimization (PSO) algorithm for solving optimization problems in power systems. The algorithm addresses a large-scale problem requiring 40-node system configuration to obtain accurate results. To handle this complexity, we employed several computational techniques including parameter tuning strategies and heuristic initialization methods. Key implementation aspects involve velocity update equations using cognitive and social parameters, position updates with boundary handling mechanisms, and fitness evaluation based on power flow calculations. The convergence behavior and robustness of the algorithm were analyzed through multiple simulation runs, with experimental results demonstrating stable performance across different operating conditions. Performance metrics include convergence speed analysis and solution quality assessment using benchmark optimization criteria. This research provides significant insights for power system optimization and serves as a valuable reference for future studies in large-scale energy system optimization.