Wind Power Generation Prediction Based on LSTM

Abstract

In recent years, with the increasing proportion of wind power generation, the impact of wind power generation on grid security is also growing. This makes the prediction accuracy of wind power generation higher and higher. This paper utilizes the LSTM model of the deep learning domain to predict wind power generation. Besides, Auto Encoder is employed to reduce the data dimension, improve the generalization ability of the model, and shorten the training time. Simulation experiments show that the LSTM model has better prediction accuracy than other machine learning model such as SVM.