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Short-Term Forecasting of City Gas Daily Demand

도시가스 일일수요의 단기예측

  • Park, Jinsoo (Department of Management Information Systems, Yong In University) ;
  • Kim, Yun Bae (Department of Systems Management Engineering, Sungkyunkwan University) ;
  • Jung, Chul Woo (Department of Systems Management Engineering, Sungkyunkwan University)
  • 박진수 (용인대학교 경영정보학과) ;
  • 김윤배 (성균관대학교 시스템경영공학과) ;
  • 정철우 (성균관대학교 시스템경영공학과)
  • Received : 2012.12.26
  • Accepted : 2013.04.29
  • Published : 2013.08.15

Abstract

Korea gas corporation (KOGAS) is responsible for the whole sale of natural gas in the domestic market. It is important to forecast the daily demand of city gas for supply and demand control, and delivery management. Since there is the autoregressive characteristic in the daily gas demand, we introduce a modified autoregressive model as the first step. The daily gas demand also has a close connection with the outdoor temperature. Accordingly, our second proposed model is a temperature-based model. Those two models, however, do not meet the requirement for forecasting performances. To produce acceptable forecasting performances, we develop a weighted average model which compounds the autoregressive model and the temperature model. To examine our proposed methods, the forecasting results are provided. We confirm that our method can forecast the daily city gas demand accurately with reasonable performances.

Keywords

References

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Cited by

  1. Forecasting Daily Demand of Domestic City Gas with Selective Sampling vol.16, pp.10, 2015, https://doi.org/10.5762/KAIS.2015.16.10.6860