Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Forecasting Daily Demand of Domestic City Gas with Selective Sampling

선별적 샘플링을 이용한 국내 도시가스 일별 수요예측 절차 개발

  • Lee, Geun-Cheol (College of Business Administration, Konkuk University) ;
  • Han, Jung-Hee (Department of Business Administration, Kangwon National University)
  • Received : 2015.07.22
  • Accepted : 2015.10.08
  • Published : 2015.10.31
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Abstract

In this study, we consider a problem of forecasting daily city gas demand of Korea. Forecasting daily gas demand is a daily routine for gas provider, and gas demand needs to be forecasted accurately in order to guarantee secure gas supply. In this study, we analyze the time series of city gas demand in several ways. Data analysis shows that primary factors affecting the city gas demand include the demand of previous day, temperature, day of week, and so on. Incorporating these factors, we developed a multiple linear regression model. Also, we devised a sampling procedure that selectively collects the past data considering the characteristics of the city gas demand. Test results on real data exhibit that the MAPE (Mean Absolute Percentage Error) obtained by the proposed method is about 2.22%, which amounts to 7% of the relative improvement ratio when compared with the existing method in the literature.

본 연구에서는 국내 도시가스 일일 수요 예측에 대한 문제를 다룬다. 정확한 일일 수요 예측은 안정적인 도시가스의 수급을 위해서 필수적인 사항으로 실제 가스 공급기관의 일상 업무에 해당한다. 본 연구에서는 수요예측 방법을 고안하기 위하여 일일 도시가스 수요 시계열에 대한 데이터 분석을 수행하였으며, 예측일 수요에 영향을 주는 주요한 요인으로 직전일 수요, 기온, 요일 등을 파악하였다. 본 연구에서는 이러한 요인들을 고려한 회귀 모형과 국내 도시가스 수요 특성에 맞는 선별적 샘플링 절차를 제안하였다. 제안 모형과 선별적 샘플링 절차로 구성된 예측 방법의 성능 검증을 위하여 실제 도시가스 수요에 대한 예측을 수행하였다. 문헌에 소개된 기존 방법과 예측 성능을 비교한 결과, 본 연구에서 제안한 방법의 평균절대백분율오차는 약 2.22%로서 개선 비율은 대략 7%에 해당한다.

Keywords

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