2026 , Volume 31, № 4, p.7-19

The article examines the influence of meteorological indicators on the level of energy consumption, which is especially important for evaluating the survivability of energy systems in extreme conditions.The study aims to develop a methodology for identifying and analyzing the correlation between ambient temperature and natural gas consumption using open data for cities and regions of the European Union. The uniqueness of the proposed approach lies in its reliance on classical statistical methods, which, unlike complex machine learning models, ensures transparency and interpretability of the identified dependencies. A distinctive feature of the method is the detailed accounting for climate data and construction of reliable meteorological models. Based on the analysis results, a regression model of daily natural gas consumption is built taking into account temperature fluctuations. The method has been tested in various locations in the European Union. The results of the study reveal a strong inverse correlation between the levels of commercial and domestic consumption and the air temperature in the consumption area; such a dependence is not observed for the industrial sector. The regression models were assessed using statistical criteria, as well as the values of the mean absolute error and the coefficient of determination. Taking into account climatic data made it possible to increase the accuracy and adequacy of natural gas consumption models in the studied areas for the commercial and domestic sectors. Future research will focus on the transition to machine learning methods and expanding the range of meteorological parameters considered.