基于模糊信息粒化和最小二乘支持向量机的风电功率波动范围组合预测模型

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Abstract The paper has put forward a combined modeling method of forecasting the range of wind power fluctuation based on fuzzy information granulation and least squares support vector machine. In this method,firstly,the theory of fuzzy information granulation is applied in processing the training samples. The valid information of components of each window,namely the minimum value,the general average value and the maximum value of each window,is extracted according to different demands. Secondly,with regard to each component,forecasting model is built respectively with least squares support vector machine and the model of each component is then optimized with adaptive particle swarm optimization. Finally,the range of wind power fluctuation is forecasted with optimized least squares support vector machine. Case study demonstrates that the combined forecasting model is able to track wind power variation to make a forecast of wind power fluctuation.

Key words： Wind power generation range of fluctuation fuzzy information granulation least squares support vector machine combined forecast

Received: 05 September 2012 Published: 22 January 2015

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TM614

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	Wang He
	Hu Zhijian
	Zhang Menglin

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Wang He,Hu Zhijian,Zhang Menglin. A Combined Forecasting Model for Range of Wind Power Fluctuation Based on Fuzzy Information Granulation and Least Squares Support Vector Machine[J]. Transactions of China Electrotechnical Society, 2014, 29(12): 218-224.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I12/218

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