A Novel Improved Particle Swarm Optimization Approach for Dynamic Economic Dispatch Incorporating Wind Power

摘要

In solving the electrical power systems dynamic economic dispatch problem, the goal is to find the optimal allocation of output power among the various generators available to serve the system load. However, new challenges about dynamic economic dispatch arise with large amounts of wind power integrated into the system. In this article, a dynamic economic dispatch model with wind power is formulated first, and then an improved particle swarm optimization approach is developed for solving the dynamic economic dispatch problem. In the optimization model, the constraints of up-spinning reserve and down-spinning reserve are introduced to deal with the influence of wind power on dynamic economic dispatch, and valve point effect is taken into account in the objective function. The proposed method combines a solution-sharing strategy with an elitist learning strategy based on the basic particle swarm optimization. The effectiveness of the proposed approach is demonstrated by comparing its performance with other approaches, including basic particle swarm optimization and the genetic algorithm. The simulation results show that the proposed method has good convergence and great economic effect. All simulations are conducted based on the 6-unit system and the 15-unit system.