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A Development of Time-Series Model for City Gas Demand Forecasting

도시가스 수요량 예측을 위한 시계열 모형 개발

Choi, Bo-Seung;Kang, Hyun-Cheol;Lee, Kyung-Yun;Han, Sang-Tae
최보승;강현철;이경윤;한상태

  • Published : 2009.10.31

Abstract

The city gas demand data has strong seasonality. Thus, the seasonality factor is the majority for the development of forecasting model for city gas supply amounts. Also, real city gas demand amounts can be affected by other factors; weekday effect, holiday effect, the number of validity day, and the number of consumptions. We examined the degree of effective power of these factors for the city gas demand and proposed a time-series model for efficient forecasting of city gas supply. We utilize the liner regression model with autoregressive regression errors and we have excellent forecasting results using real data.

Keywords

City gas;demand forecast;regression with autoregressive errors;validity day effect;elasticity of temperature

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