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A novel modeling approach for hourly forecasting of long-term electric energy demand

机译：每小时预测长期电力需求的新颖建模方法

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摘要

In this study, a novel mathematical method is proposed for modeling and forecasting electric energy demand. The method is capable of making long-term forecasts. However, unlike other long-term forecasting models, the proposed method produces hourly results with improved accuracy. The model is constructed and verified using 26-year-long real-life load data (4 years with hourly resolution) obtained from the Turkish Electric Power Company. The overall method consists of a nested combination of three subsections for modeling. The first section is the coarse level for modeling variations of yearly average loads. The second section refines this structure by modeling weekly residual load variations within a year. The final section reaches to the hourly resolution by modeling variations within a week, using a novel 2-D mathematical representation at this resolution. The adoptions of such nested forecasting methodology together with the proposed 2-D representation for hourly load constitute the novelties of this work. The major advantage of the proposed approach is that it enables the possibility of making short-, medium-, and long-term hourly load forecasting within a single framework. Several mathematical functions are applied as models at each level of the nested system for achieving the minimal forecasting error. Proposed model functions with their corresponding forecasting accuracies are presented in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE).
机译：在这项研究中，提出了一种新的数学方法来建模和预测电能需求。该方法能够进行长期预测。但是，与其他长期预测模型不同，该方法可产生每小时的结果，且准确性更高。该模型是使用从土耳其电力公司获得的长达26年的实际负载数据（每小时分辨率为4年）构建和验证的。整体方法由三个小节的嵌套组合组成，用于建模。第一部分是模拟年平均负荷变化的粗略水平。第二部分通过对一年内每周的剩余负荷变化进行建模来完善此结构。最后一部分通过使用一个新颖的二维数学表示法在一周内模拟变化来达到小时分辨率。这种嵌套式预测方法的采用以及每小时负荷的建议二维表示法构成了这项工作的新颖性。提议的方法的主要优点在于，它使在单个框架内进行短期，中期和长期的每小时负荷预测成为可能。在嵌套系统的每个级别上，将几个数学函数用作模型，以实现最小的预测误差。根据均方根误差（RMSE）和平均绝对百分比误差（MAPE）提出了建议的模型函数及其相应的预测精度。

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