Abstract
Electric power consumption along with a large variety of factors affecting it can be forecasted and modelled by using econometric forecasting methods, including time series and correlation and regression analysis. For the purpose of this research, electric power consumption in the Moscow Region, Russia, was modelled with consideration of economic and climate factors based on 2019–2020 power usage data. A multiplicative model for regional electric power consumption and correlations between electric power consumption and an air temperature as well as a total number of cloudy days a month were built. The results will be helpful for analyzing and forecasting of processes involved in power consumption.
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