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Short Term Wind Power Forecasting Using Autoregressive Integrated Moving Average Modeling
Proceedings of the Fifteenth International Middle East Power Systems Conference, Alexandria, Egypt, December 23-25, 2012 (MEPCON'12) (2012)
  • Almoataz Youssef Abdelaziz
Abstract

Wind energy is one of the most promising electricity generating sources as a clean and free alternate compared with the conventional power plants and due to the volatility feature in the wind speeds it will reflect some problems in power systems reliability particularly if the system is deeply penetrated by wind farms. Therefore, Wind power forecasting issue became and is still an important scope that will help in economic dispatch (ED), unit commitment (UC) purposes to get more reliable and economic systems. This paper introduces short term wind power forecasting model, based on autoregressive integrated moving average (ARIMA) which will be applied to hourly wind data from Zaafarana 5 project in Egypt. The proposed model successfully outperforms the persistence model with significant improvement up to 6 hours ahead.

Keywords
  • Wind forecasting,
  • time series analysis,
  • ARMA,
  • Box-Jenkins model
Publication Date
December 23, 2012
Citation Information
Almoataz Youssef Abdelaziz. "Short Term Wind Power Forecasting Using Autoregressive Integrated Moving Average Modeling" Proceedings of the Fifteenth International Middle East Power Systems Conference, Alexandria, Egypt, December 23-25, 2012 (MEPCON'12) (2012)
Available at: http://works.bepress.com/almoataz_abdelaziz/39/