HYBRID GA-PSO ALGORITHM FOR WIND FARM MICRO-SITING IN COMPLEX TERRAIN
A hybrid GA-PSO algorithm combining improved genetic algorithm(GA)and particle swarm optimization(PSO)is proposed to optimize the wind turbine layout scheme in complex terrain.Taking a real complex terrain in Hunan Province as the target,the full wind direction numerical simulation of the wind farm is carried out,and the potential wind energy distribution of the region is evaluated by combining long-term observed wind data,and the improved GA(IGA)considering grid preprocessing,time-varying mutation rate,uniqueness and parallelization is proposed for cluster optimization of the wind turbine layout scheme,based on which the further optimization is carried out using the PSO algorithm.Uncertainty analysis is performed for the effect of the wake model and objective function model on the optimization results.The results show that the proposed GA-PSO algorithm improves 16.4%,12.9%,and 5.1%over the greedy algorithm,GA,and IGA,respectively,in wind farm micro-siting in complex terrain.
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