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Wind speed forecasting based on ARFIMA-EGARCH model

Xueting Liu, Youquan Wang

Because of the important technological and economic impacts of wind speed onwind power generation and the increasing as a renewable energy source in many countries of wind power, providing accurate wind speed prediction algorithms has become increasingly significant to the planning of wind speed plants, the scheduling dispatchable generation and tariffs in the day-ahead electricity market and the operation of power systems. In this paper, a strategy, which adopts ARFIMA-EGARCH model is presented for wind speed forecasting. The results show that ARFIMAEGARCH model, which combines both the long memory time series and the conditional heteroscedastic processes, possesses higher accuracy than the classical approach towards wind forecasting.