基于EMD分解和集对分析的风电功率实时预测

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Abstract The randomness and volatility of wind power time series make it difficult to achieve the desired multi-step prediction accuracy.Therefore, a model of real-time prediction for wind power based on empirical mode decomposition(EMD) and set pair analysis is presented.The proposed wind power sequences are firstly decomposed into a series of functions with more stationary variation by the EMD technique.Then these functions are divided into three components(high-middle-low frequency components) according to their run-lengths by the extreme point division method.Finally, three prediction models are built under the basis of their respective variation rules, and the results of three prediction models are reconstructed with the original wind power prediction value, this model achieves multi-step prediction by rolling prediction.The data from Three different wind farms with different installed capacity are used for simulate experiment.The results show that the proposed approach possesses with higher accuracy and the prediction performance is satisfied.

Key words： Wind power real-time prediction empirical mode decomposition(EMD) rank and set pair analysis

Received: 26 June 2015 Published: 21 November 2016

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TM614

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	Yang Mao
	Chen Yulin

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Yang Mao,Chen Yulin. Real-Time Prediction for Wind Power Based on EMD and Set Pair Analysis[J]. Transactions of China Electrotechnical Society, 2016, 31(21): 86-93.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I21/86