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Short-term prediction of wind power combining GM(1,1) model with cloud model

机译:通用通用通用通用电力的短期预测(1,1)模型与云模型

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This paper proposes a new method to predict wind power of wind farm using the combination of GM(1,1) model and cloud model. The original wind power signals are decomposed into high frequency part and low frequency part by wavelet decomposition. Cloud model is constructed to predict wind power of high frequency part and GM(1,1) model is used to predict wind power of low frequency part. The predicted power can be obtained by high frequency part and low frequency part. The simulation example shows that the method proposed in this paper is obviously better than single predicting method and the effectiveness of the method is verified by the predicting results.
机译:本文提出了一种使用GM(1,1)模型和云模型的组合来预测风电场风电的新方法。原始风电信号通过小波分解分解成高频部分和低频部分。构造云模型以预测高频部件的风力,GM(1,1)模型用于预测低频部分的风力。预测功率可以通过高频部分和低频部分获得。模拟示例表明,本文提出的方法显着优于单预测方法,并通过预测结果验证该方法的有效性。

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