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Application and Improvement of Smoothing Model with Winston Linearity and Seasonal Index in Prediction of Power Load

机译:温斯顿线性和季节指数平滑模型在电力负荷预测中的应用与改进

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Owing to periodicity rises and falls with year, month or day for unit, and tendency that moves upward year by year, power load fit for in with smoothing model with Winston linearity and seasonal index predicting. On the other hand, this model is the most sensitive as for the unusual value in power load data, and frequently leads to calculating that the result is contrary with the development trend of actual power load. In the light of power load appearing the complicated combined characteristic with period and growth, it is led in this paper that smoothing model with Winston linearity and seasonal index is used power load prediction. For enhancing stability of this method, the improved model is set up to get stronger unusual data digestion ability, and prediction result fits the overall development trend of power load further. This improved model could adapt to few unusual date, avoid contrary conclusion, and advance prediction precision. Furthermore, the power load data of Shanghai electric network is applied to carry on the real predicting process, and to prove the stability and practicality of the improved model.
机译:由于单位的周期性随着年,月或日的上升和下降,以及逐年上升的趋势,电力负荷适合于具有温斯顿线性和季节性指数预测的平滑模型。另一方面,该模型对于电力负荷数据中的异常值最为敏感,经常导致计算结果与实际电力负荷的发展趋势相反。鉴于电力负荷呈现出具有周期和增长的复杂组合特征,本文提出采用温斯顿线性度和季节指数的平滑模型进行电力负荷预测。为了提高该方法的稳定性,建立了改进的模型以获得更强的异常数据消化能力,并且预测结果进一步适应了电力负荷的总体发展趋势。这种改进的模型可以适应很少的异常日期,避免得出相反的结论,并提高预测精度。进一步,利用上海电网的电力负荷数据进行了真实的预测过程,证明了改进模型的稳定性和实用性。

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