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Modelling the load curve of aggregate electricity consumption using principal components

机译:使用主成分模拟总用电量的负荷曲线

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摘要

Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compared with those produced by the Fourier and Constrained Smoothing Spline estimators. The PC method represents a much simpler and attractive alternative to modelling electricity consumption since it is extremely easy to compute, significantly reduces the number of variables to be considered, and generally increases the accuracy of electricity consumption forecasts. As an additional advantage, the PC method is able to accommodate relevant exogenous variables such as daily temperature and environmental factors, and is extremely versatile in computing out-of-sample forecasts.
机译:由于石油是一种对环境造成重大影响的不可再生资源,并且其最常见的用途是生产电力可燃物,因此对电力消耗进行建模的可靠方法可以有助于更合理地使用这种碳氢燃料。在本文中,我们将主成分(PC)方法用于基于总用电量的小时数据对意大利,法国和希腊的负荷曲线进行建模。将PC方法获得的经验结果与傅里叶和约束平滑样条估计器产生的结果进行比较。 PC方法代表了用电量建模的一种更简单,更有吸引力的替代方法,因为它非常易于计算,可以显着减少要考虑的变量数量,并且通常可以提高用电量预测的准确性。 PC的另一个优点是,它能够适应相关的外生变量,例如日常温度和环境因素,并且在计算样本外预测方面非常通用。

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