Natural gas demand forecasting based on a subdivided forecasting model and rule-based calibration
by Gisun Jung; Jinsoo Park; Young Kim; Yun Bae Kim
International Journal of Oil, Gas and Coal Technology (IJOGCT), Vol. 32, No. 4, 2023

Abstract: In South Korea, with growing volatility in natural gas demand owing to the implementation of eco-friendly energy policies, accurate demand forecasting is becoming more essential. Natural gas demand in South Korea is divided into city and power generation gas. To forecast the volatile energy demand considering daily and regional characteristics, detailed mathematical models and rules to calibrate subtle variations are needed. Power generation gas is more difficult to predict because of exceptional conditions changing the demand pattern owing to sudden weather changes. We propose a subdivided mathematical model that reflects use and daily and regional characteristics. Additionally, adopting rule-based calibration improved forecasting accuracy compared with using only the mathematical model. We performed a forecasting test for one year and confirmed that the average error rate was approximately 2.9%, a substantial reduction in mean absolute percentage error (MAPE) compared to the previously employed moving average method, which validates our proposed method. [Received: October 26, 2021; Accepted: August 13, 2022]

Online publication date: Tue, 14-Mar-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Oil, Gas and Coal Technology (IJOGCT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com