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基于频域分解的短期风电负荷预测

, PP. 66-72

Keywords: 频域分解,提升小波,风电,负荷预测

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Abstract:

为了克服风电的不规则性和提高风电负荷预测的精度,将频域分解的方法运用在风电负荷预测中可以找到风电的部分规律和在一定程度上克服风电的不规则性。通过对原始负荷数据的频域分解,将数据分解成日周期、周周期、低频和高频四个部分。日周期的部分用神经网络的方法训练和预测。低频部分用一元线性回归的方法预测。高频部分用提升小波和神经网络相结合的方法训练和预测。最后将各部分的预测结果加起来,这样就实现了风电负荷的高精度预测。本文中用实际数据进行仿真,实验结果表明,基于频域分解的方法可以比较好地找到风电的规律,有利于通过不同的方法对不同的部分进行短期负荷预测,很大程度地提高预测的精度,测试表明该方法用于风电负荷预测是有效可行的。

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