A Comparison of Forecasting Methods for Carbon Dioxide Emissions from Coal Fuel in Power Generation - Mingkwan, Yutthachai (KKU Science Journal, 2026)
This research aims to develop forecasting models and compare forecasting methods for carbon dioxide emissions from coal fuel in power generation. The data were obtained from the Energy Policy and Planning Office, Ministry of Energy, covering the period from January 2009 to December 2024, with a total of 192 months. The data were divided into two sets. The first set, covering January 2009 to December 2023, with a total of 180 months, was used to construct forecasting models using four methods: Box and Jenkins method, Winters’ additive method, Winters’ multiplicative method, and Holt’s method. The second set, covering January to December 2024, with a total of 12 months, was used for comparing forecasting performance based on the lowest root mean square error and mean absolute percentage error. The results indicate that Winters’ multiplicative method was the most appropriate method for forecasting, as it yielded the lowest forecasting error.