关键词: 风力发电, 风电功率, 风速, 时间序列, 神经网络

Abstract:

To solve the problem that non-linear relationship between wind speed and wind power could amplify prediction error, the improved model for wind speed and wind power forecasting in short term was proposed based on time series and back propagation artificial neural network (BPANN). First, the time series model was built to forecast wind speed. Then the BP-ANN model of wind speed-to-power was set up and the predicted wind speed was input into the model to obtain wind power. Taking a wind power plant as an example, mean absolute error and correlation index of the improved model and the conventional model were compared, and the result showed that the improved model could improve wind power forecasting accuracy.

Key words: wind power generation, wind speed, BP-ANN, wind power, time series