基于多位置NWP与主成分分析的风电功率短期预测

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Abstract Numerical weather prediction (NWP) plays an important role in the accuracy of the short-term wind power prediction models.Considering NWP information of multiple locations around a wind farm,this paper introduces a method based on the cluster analysis and the principal component analysis to study the short-term prediction of the wind power generating capacity.The sample in the historical data closest to the NWP of the forecast day is extracted by the clustering analysis.Then the principal component analysis of the sample information is proceeded to obtain the parameters which reflects the characteristics of the wind farm.Simulation is performed consideringthe wind power generation of Yilan wind farm.The results show that the method is effective and its precision improves 4.65% than the prediction model based on NWP of single location.

Key words： Wind power prediction numerical weather prediction multiple locations principal component analysis cluster analysis

Received: 20 November 2014 Published: 13 April 2015

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TM614

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	Wang Lijie
	Dong Lei
	Gao Shuang

Cite this article:

Wang Lijie,Dong Lei,Gao Shuang. Wind Power Short-term Prediction Based on Principal Component Analysis of NWP of Multiple Locations[J]. Transactions of China Electrotechnical Society, 2015, 30(5): 79-84.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2015/V30/I5/79

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