Robust Control of High-Permeability Industrial Power Plants Based on the Optimised GA-PSO Approach
In order to make up for the problem of low robust scheduling of wind power output of traditional particle swarm(PSO)algorithm,a high permeability power station robustness control based on optimised GA-PSO method is designed by optimising PSO way through genetic algorithm(GA).Through the PSO algorithm and cross-variance fusion form to PSO fast convergence effect,to avoid particles produce local optimal.The results of the algorithmic research carried out show that the robust control method in this paper exhibits stronger robustness than the traditional control mode,ensuring that the power plant achieves the safe and stable control goal.After continuously improving the number of wind farms,the distribution range of wind farms is also further expanded,which improves the stability of wind power output,reduces the degree of impact of the power station,resulting in a significant reduction in the cost of system risk.The method has the advantage of fast convergence of PSO and eliminates the defect of the existence of local optimum of particles.
power stationautomatic controlparticle swarm algorithmgenetic algorithmrobustnessrisk cost
万方数据
维普
