A wind power prediction method based on extreme learning machine model
LI Guoquan
LI Lingling
Abstract：Wind energy has strong volatility and randomness,and wind power also has the same characteris-tics.Therefore,this study proposes an improved limit learning model to improve the utilization of wind energy.Firstly,this paper proposes to optimize the parameters by crow search algorithm,and through the test of con-vergence performance,crow search algorithm has a greater advantage in global search ability as well as local exploitation ability.Secondly,the input and output variables of the model function are determined and then compared with other models using several evaluative metrics respectively.Finally,the prediction results of the improved extreme learning machine model are evaluated and analyzed.The prediction results show that the prediction accuracy and stability of the Improved Extreme Learning Model are higher than other models.
Keywords：new energywind power predictionextreme learning machinecrow search algorithm
Publication Date：2024-06-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 75-82 )