論文

査読有り
2020年11月10日

Event Effects Estimation on Electricity Demand Forecasting

Energies
  • Kei Hirose
  • ,
  • Keigo Wada
  • ,
  • Maiya Hori
  • ,
  • Rin-ichiro Taniguchi

13
21
開始ページ
5839
終了ページ
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/en13215839
出版者・発行元
MDPI AG

We consider the problem of short-term electricity demand forecasting in a small-scale area. Electric power usage depends heavily on irregular daily events. Event information must be incorporated into the forecasting model to obtain high forecast accuracy. The electricity fluctuation due to daily events is considered to be a basis function of time period in a regression model. We present several basis functions that extract the characteristics of the event effect. When the basis function cannot be specified, we employ the fused lasso for automatic construction of the basis function. With the fused lasso, some coefficients of neighboring time periods take exactly the same values, leading to stable basis function estimation and enhancement of interpretation. Our proposed method is applied to the electricity demand data of a research facility in Japan. The results show that our proposed model yields better forecast accuracy than a model that omits event information; our proposed method resulted in roughly 12% and 20% improvements in mean absolute percentage error and root mean squared error, respectively.

リンク情報
DOI
https://doi.org/10.3390/en13215839
URL
https://www.mdpi.com/1996-1073/13/21/5839/pdf
ID情報
  • DOI : 10.3390/en13215839
  • eISSN : 1996-1073

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