Ultra-short Term Wind Power Prediction Based on ARIMA Model Based on Data Preprocessing
In order to improve the accuracy and stability of short-term wind power forecasting,a wind power ultra-short-term forecasting algorithm based on preprocessed data and ARIMA time series autoregressive integrated moving average model is proposed in this paper.Taking the actual measurement data from a wind farm in Heilongjiang Province as an example,the wind tower data is initially preprocessed,addressing anomalies in the wind farm data and analyzing the correlation of factors influencing wind power output.The obtained data is differentially processed to suit the requirements of the ARIMA model for prediction.Results indicate that this method effectively enhances prediction accuracy and coverage.
wind power forecastingARIMA modeltime series forecasting
NETL
NSTL
万方数据
