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海量数据下的电力负荷短期预测

DOI: 10.13334/j.0258-8013.pcsee.2015.01.005, PP. 37-42

Keywords: 大数据,云计算,负荷预测,局部加权线性回归

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Abstract:

该文研究海量数据下的短期电力负荷预测方法,基于局部加权线性回归和云计算平台,建立并行局部加权线性回归模型。同时,为剔除坏数据,采用最大熵建立坏数据分类模型,保证历史数据的有效性。实验数据来自已建的甘肃某智能园区。实验结果表明,提出的并行局部加权模型用于短期电力负荷预测是可行的,平均均方根误差为3.01%,完全满足负荷预测的要求,并极大地减少了负荷预测时间,提高预测精度。

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