基于RVM与ARMA误差校正的短期风速预测

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Abstract To improve the accuracy of wind speed forecasting, a method based on relevant vector machine(RVM) and auto-regressive moving average(ARMA) error correcting is proposed. Firstly, the nonlinear model of influencing factors and wind speed of the next 24 hours are built based on RVM, and genetic algorithm(GA) is used to ensure the optimization of model parameters. Secondly, the error series of wind speed forecasted by RVM model are adjusted by ARMA model. Finally, the forecasted wind speed is amended by the forecasting errors, which are generated by ARMA model. The wind speed forecasting results of any day in the future for a wind farm in the Jiangsu province demonstrate that the proposed method is reasonable and effective.

Key words： Wind speed forecasting error correcting RVM model ARMA model

Received: 30 July 2010 Published: 20 March 2014

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TM614

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	Sun Guoqiang
	Wei Zhinong
	Zhai Weixing

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Sun Guoqiang,Wei Zhinong,Zhai Weixing. Short Term Wind Speed Forecasting Based on RVM and ARMA Error Correcting[J]. Transactions of China Electrotechnical Society, 2012, 27(8): 187-193.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I8/187

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