
Today, energy consumption plays a decisive role in the qualitative and quantitative development of human life. One of the energy sources that aligns with development, economic prosperity, and the acquisition of climatic comfort is natural gas. This energy source, especially in cold regions of the country, is essential for providing thermal comfort and requires proper management. Effective management of this fossil energy source depends on awareness and accurate forecasting of its demand. For this reason, the demand for natural gas in Zanjan city, one of the cold cities in Iran, was studied and modeled. Two groups of data—weather elements and natural gas consumption—over a period of 9 years (2013–2021) on a daily scale were used for this study. CurveExpert software and regression methods were employed to model the demand for natural gas in the city. Based on the most accurate pattern, temperature was selected as the only independent variable in the chosen model. Polynomial regression, with a correlation coefficient of 0.94 (coefficient of determination of 89.03%), was selected as the final model. The analysis revealed that the percentage increase in natural gas consumption per one-degree decrease in temperature varies across different temperature ranges. From 22°C to 16°C, the highest percentage increase in consumption was observed, while from 0°C to -5°C, the lowest percentage increase per one-degree decrease in temperature was recorded. The turning point and the beginning of issues related to natural gas shortages in Zanjan city were identified to occur at temperatures below -7°C.
natural gas, Geography (General), polynomial regression, zanjan., G1-922, modeling
natural gas, Geography (General), polynomial regression, zanjan., G1-922, modeling
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