Abstract
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.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
Reference114 articles.
1. Model Estimation of ARMA Using Genetic Algorithms: A Case Study of Forecasting Natural Gas Consumption
2. Exploring the production of natural gas through the lenses of the ACEGES model
3. Will natural gas be competitive fuel? (in Polish: Czy gaz ziemny będzie paliwem konkurencyjnym?);Szurlej;Rynek Energii,2015
4. Poland’s Energy Policy until 2050 (in Polish: Polityka Energetyczna Polski do 2050 roku);Ciechanowska;Naft. Gaz,2014
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