A Short-Term Wind Power Prediction Model Based on Similar Historical Meteorological Data and WNN-HHO-BP Neural Network

Abstract

A short-term wind power prediction model based on similar historical meteorological data and WNN-HHO-BP neural network is proposed. Firstly, K-means clustering is used to classify the daily meteorological data into three classes as well as wavelet decomposition to decompose the data. Then, a BP neural network with Harris Hawk optimization algorithm and a BP neural network only are used for short-term prediction of wind power, and finally, the prediction results are derived and compared.