In March 2020, a lockdown was imposed due to a global pandemic, which contributed to changes in the structure of the consumption of natural gas. Consumption in the industry and the power sector decreased while household consumption increased. There was also a noticeable decrease in natural gas consumption by commercial consumers. Based on collected data, such as temperature, wind strength, duration of weather events, and information about weather conditions on preceding days, models for forecasting gas consumption by commercial consumers (hotels, restaurants, and businesses) were designed, and the best model for determining the impact of the lockdown on gas consumption by the above-mentioned consumers was determined using the MAPE (mean absolute percentage error). The best model of artificial neural networks (ANN) gave a 2.17% MAPE error. The study found a significant decrease in gas consumption by commercial customers during the first lockdown period.
The scale of methane emissions from gas distribution systems has serious consequences for energy security, ensuring the security of natural gas transmission and reducing gas losses in transport. That is why it is important to determine the scale of such emissions from individual elements of the infrastructure. It has been confirmed that such emissions have a significant effect on the military security of EU co untries. The emission factor (EF) is affected by many other causes. The best method of calculating the EF is one that takes into account the most variables. A theoretical method of determining the EF has been developed, taking into consideration the age of the equipment as well as pressure, temperature and speed. When comparing the methods in the literature to date, one has to bear in mind that none of them describes the variables that affect the magnitude of the EF. To map an actual emission, it is crucial to have data that describe the gas infrastructure component under analysis, along with the most precise information available to characterise the operating conditions.
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