Accurate forecasting of natural gas load forecasting is of great practical significance to balance supply and demand of gas system. Load forecasting is categorized in long-term, mid-term and short-term. Among them, mid-term load forecasting that monitors monthly operations is of decisive significance to urban gas pipe network planning, gas engineering project construction and design. In this study, we adopt Prophet model that reflects the seasonal fluctuations and holidays influence to forecasting the monthly gas load of urban gas and compare the results with the other two forecasting methods such as autoregressive integrated moving average model (ARIMA) and exponential smoothing prediction method (ESM). The models were trained and tested on gas consumption data gathered in one central city in China from 2017 to 2021. The result shows that an increasing trend with an average growth rate between 10% and 20% year by year, a decreasing trend at an average rate of 14.9% on legal holiday. According to this study, the Prophet model has an excellent performance in monthly natural gas forecasting.
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Acknowledgments
This work was supported by the Key Research & Development and Promotion Project of Henan Province (Grant No.212102310279) and the Science and Technology Innovation Project of China Resources Gas (Grant No.RKT202101).
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Translated from Khimiya i Tekhnologiya Topliv i Masel, No. 5, pp. 91–96 September–October, 2022.
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Wang, P., Zhao, R., Guo, Y. et al. Urban Gas Load Forecasting Based on Time Series Methods. Chem Technol Fuels Oils 58, 828–838 (2022). https://doi.org/10.1007/s10553-022-01458-5
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DOI: https://doi.org/10.1007/s10553-022-01458-5