Multi-Objective Optimization of Wind Farm Dispatch Problem by Double-Layer Particle Swarm Optimization Algorithm

In the process of power dispatch of the wind turbines, the frequent start-up and shut-down will accelerate the performance degradation of the wind turbines. The strategy of adjusting the power output of each wind turbine through the pitch angle of the blade control system will also reduce the stability margin of wind turbines. In order to reduce the loss caused by frequent changes of start-up and shut-down and improve the stability margin of wind turbines, the double-layer particle swarm optimization (DLPSO) algorithm is proposed, including the binary particle swarm optimization (BPSO) algorithm in the outer layer, and the self-adjusting chaotic particle swarm optimization (SACPSO) algorithm in the inner layer. The wind turbine dispatch model is established, wherein the times of start-up and shut-down, and the mean value of the power limitation index are taken into account in the objective function. Based on the wind turbine dispatch model, the DLPSO algorithm is employed to solve the wind turbine dispatch problem. Extensive experimental results are finally presented to demonstrate the validity and effectiveness of the proposed DLPSO algorithm and the wind turbine dispatch model.