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Daily electrical energy consumption: Periodicity, harmonic regression method and forecasting

机译:每日电能消耗:周期性,谐波回归方法和预测

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摘要

This study starts with a brief analysis of the global electricity market with special reference to the Turkish market. Next, the daily electricity consumption amounts in Turkey between 2012 and 2016 are examined by using statistical tools. Furthermore, the periodicity in the data is discovered. The periodicity, which has an impact not only in the electricity market but also in other sectors of the economy, is an important indicator for planning and policy-making. Periodicity is easier to observe depending on seasonal impacts. However, what is important is to detect hidden periodicity. The main contribution of this study is to detect the hidden periodicity with a rather novel approach in the electricity industry. The proposed periodicity test based on the periodogram ordinate has two major advantages. First, the periodograms are invariant to the model selection. Secondly, the distributions of the normalized periodograms and therefore critical values do not depend on the sample size. Moreover, the forecasting performance of the model for Turkish electricity consumption seems to be better compared to the standard time series model.
机译:本研究首先对全球电力市场进行了简要分析,并特别参考了土耳其市场。接下来,使用统计工具检查土耳其在2012年至2016年之间的每日用电量。此外,发现数据中的周期性。周期性不仅影响电力市场,而且影响其他经济部门,是规划和决策的重要指标。根据季节的影响,周期性更容易观察。但是,重要的是检测隐藏的周期性。这项研究的主要贡献是用一种相当新颖的方法来检测电力行业中的隐藏周期性。提议的基于周期图纵坐标的周期性测试有两个主要优点。首先,周期图对于模型选择是不变的。其次,归一化周期图的分布以及因此的临界值不取决于样本量。此外,与标准时间序列模型相比,该模型对土耳其用电量的预测性能似乎更好。

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  • 来源
    《Energy》 |2020年第15期|116524.1-116524.10|共10页
  • 作者单位

    Department of Statistics Faculty of Science Ankara University Ankara Turkey;

    Department of Econometrics Faculty of Economics and Administrative Sciences Atatuerk University Erzurum Turkey;

    Department of Mathematical Sciences Faculty of Social Sciences University of Southampton Southampton UK;

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  • 正文语种 eng
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