Design of an Ultra-Short-Term Wind Power Forecasting Model Combined with CNN and LSTM Networks

Abstract

Accurate short-term wind power forecasting has a significant impact to economic dispatch, which ensures the efficiency and smooth operation of power system. In this paper, a hybrid wind power forecasting method based on a typical algorithm of feedforward neural network, convolutional neural network (CNN) and a time circulation neural network, and long short-term memory network (LSTM) models is proposed. It aims to improve the accuracy of ultra-short-term wind power forecasting.