Optimization Algorithm for Micro Site Selection of Complex Terrain Wind Farm
China possesses abundant and widely distributed wind energy resources,with the development of wind energy in complex terrains becoming increasingly significant.In the development of wind energy,micro-siting is of critical importance.Due to the low efficiency of traditional micro-siting optimization methods for wind farms in complex terrains,and the challenges in fully harnessing wind resources,this paper introduces two more effective optimization approaches.Firstly,the Grey Wolf Optimization(GWO)algorithm is applied to optimize wind farm siting.This method focuses on optimizing individual wind turbines based on their capacity factor,with the objective of increasing overall electricity generation.The optimized wind turbines collectively form the complete layout of the wind farm.Specifically tailored for micro-siting optimization in complex terrains,this method significantly enhances optimization efficiency and effectively achieves its objectives.Secondly,a finite scheme optimization is utilized.This involves analyzing the capacity factor and wind direction distributions at certain heights within the wind farm,and proposing various layout schemes.The optimal scheme is selected based on the principle of maximizing electricity generation.This approach directly identifies the best outcome,thereby reducing computational resource expenditure.
Complex TerrainMicro Site SelectionGrey Wolf Optimization AlgorithmLimited OptimizationCapacity Factor
万方数据
维普
