Hybrid Particle Swarm Optimization Approach for Solving OPF Problem

This paper presents a hybrid particle swarm optimization algorithm (HPSO) as a modern optimization tool to solve the optimal power flow (OPF) problem. The objective functions considered are the system real power losses, fuel cost, voltage deviation and voltage stability index. The proposed algorithm makes use of the PSO, known for its global searching capabilities, to allocate the optimal control settings. PSO algorithm is combined with conventional newton/IPM algorithm to form HPSO. A hybrid inequality constraint handling mechanism that preserves only feasible solutions is incorporated in the proposed approach. To demonstrate its robustness, the proposed algorithm was tested on the IEEE 30-bus system. Several cases were investigated to test and validate the consistency of detecting optimal solution for each objective. The results show that the proposed hybrid method successfully and efficiently handles the equality and inequality constraints for PSO algorithms. Key words— Constraints handling, hybrid method, Newton-like method, IPM method, optimal power flow, PSO.