结合GM(1,1)模型和云模型的风电短期预测

Xiaojuan Han, Fangyuan Meng, Zhihui Song, Xiangjun Li
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引用次数: 3

摘要

本文提出了一种将GM(1,1)模型与云模型相结合的风电场风电功率预测新方法。采用小波分解的方法将原始风电信号分解为高频部分和低频部分。构建云模型预测高频部分风电功率,采用GM(1,1)模型预测低频部分风电功率。预测功率可通过高频部分和低频部分得到。仿真实例表明,本文提出的方法明显优于单一的预测方法,预测结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term prediction of wind power combining GM(1,1) model with cloud model
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.
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