An Effective Particle Swarm Optimization Algorithm with Social Weight in Solving Economic Dispatch Problem Considering Network Losses

Abstract

This paper proposes an effective particle swarm optimization algorithm with social weight (ESWPSO) to solve economic dispatch problem in power system. Many nonlinear characteristics of cost function and operational constraints are all considered for practical operation. The extremum disturbance operator in ESWPSO effectively contributes to finding better solutions by generating random points in promising area. The penalty strategy is adopted to help particles satisfy the dynamic power balance constraints. The effectiveness and feasibility of ESWPSO are demonstrated by two power system cases. Compared with previous literature, the experiment results show ESWPSO can fast find higher quality solutions.