Short-term Wind Speed Forecast Using ARIMA Based on EEMD Decomposition

Abstract

Wind speed prediction of the wind power plant has an important influence on the stability and safe operation of the power system. Because the wind speed series is intermittent and random, a combination model of EEMD-ARIMA is proposed to predict ultra-short-term wind speed. The advantage of the prediction model mentioned in this paper is to deal with the problem of large prediction errors caused by the instability of the original wind speed series. First, the ensemble empirical mode decomposition (EEMD) is used to decompose the series, and then the autoregressive moving average (ARIMA) is used to predict the components. Through the example analysis, it can be seen that the prediction model mentioned in this paper is more accurate than the traditional ARIMA model in predicting short-term wind speed.