title: ÐÐ½Ð°Ð»Ð¸Ð· Ð¸ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ»ÐµÐºÑÑÐ¾Ð±Ð°Ð»Ð°Ð½ÑÐ° Ð Ð¤ Ð½Ð° ÑÑÐ¾Ð²Ð½Ðµ Ð¼ÐµÐ·Ð¾ÑÐ¸ÑÑÐµÐ¼ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÐ°ÐºÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð¸ ÑÑÐµÐ½Ð´Ð¾Ð²Ð¾Ð³Ð¾ Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Analysis and forecasting of the electrical balance of the Russian Federation at the mesosystem level using factor and trend approaches
Creators: name: Ð©ÐµÐ½Ð¸ÐºÐ¾Ð², ÐÐ³Ð¾Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÐ°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ»ÐµÐºÑÑÐ¾Ð±Ð°Ð»Ð°Ð½Ñ
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
ÑÐ½ÐµÑÐ³ÐµÑÐ¸ÑÐµÑÐºÐ¸Ð¹ ÑÐµÐºÑÐ¾Ñ
Ð¼ÐµÐ·Ð¾ÑÐ¸ÑÑÐµÐ¼Ñ
electrical balance
forecasting
energy sector
mesosystems

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description: The aim of the study is to develop an effective methodology for analyzing and forecasting the electrical balance of the Russian Federation at the mesosystem level to ensure the stability of the energy sector and the economic stability of the country. The subject of the WRC is methods of analysis and forecasting of the electrical balance of the Russian Federation at the level of mesosystems using factorial and trend approaches. Research methods: a complex combination of theoretical (description, generalization) and practical (visualization, analysis, classification, comparison, modeling) research methods. The main results of the study are the methodology of forecasting the electrical balance at the mesosystem level, forecasting models using a factorial and trend approach. The scope of application of the results of the WRC: the energy complex of the Russian Federation. The scientific novelty is the implementation of the prediction of electrical balance using a trend and factor approach, classification into mesosystems. As a result of this study, a methodology for forecasting the electrical balance of the Russian Federation was developed, including the use of trend and factor approaches, as well as machine learning and ARIMA methods. This methodology makes it possible to obtain forecasts of electricity generation and consumption at the mesosystem level, which is an important tool for planning and managing the countrys energy resources.