Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources
Load Forecasting and Smart Grid Resilience Enhancement|更新时间:2026-09-16
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Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources
Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources
全球能源互联网(英文)2026年9卷第3期
作者机构:
1. Institute of Engineering and Technology, South Ural State University,Chelyabinsk,Russia,454080
2. First Deputy General Director of Uralenergos byt LLC,Chelyabinsk,Russia,454080
Saidjon Tavarov, Aleksandr Sidorov, Andrey Svyatykh, 等. Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources[J]. 全球能源互联网(英文), 2026,9(3).
Saidjon Tavarov, Aleksandr Sidorov, Andrey Svyatykh, et al. Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources[J]. Global Energy Interconnection, 2026, 9(3).
Saidjon Tavarov, Aleksandr Sidorov, Andrey Svyatykh, 等. Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources[J]. 全球能源互联网(英文), 2026,9(3).DOI: 10.14171/j.2096-5117.gei.2026.03.008.
Saidjon Tavarov, Aleksandr Sidorov, Andrey Svyatykh, et al. Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources[J]. Global Energy Interconnection, 2026, 9(3).DOI: 10.14171/j.2096-5117.gei.2026.03.008.
Forecasting the average daily and during the hours of maximum electric load based on the data of the average monthly electricity consumption with single and other energy sources
The article is devoted to the determination of the average daily and during the hours of maximum electric load according to the data of electricity consumption
taking into account the generalized coefficient Ai for apartment buildings and individual residential buildings in Chelyabinsk and the cities of Dushanbe and Khorog of the Republic of Tajikistan. The results of modeling the average daily electric load taking into account the developed generalized coefficient Ai show that the specific power values for apartments in apartment buildings and in individual residential buildings in the city of Chelyabinsk and the cities of Dushanbe and Khorog of the Republic of Tajikistan are overestimated
taking into account the applicability in the Republic of Tajikistan of the same standard values of specific electric loads(SEL) of apartments in apartment buildings (AB) as in the Russian Federation. According to the results of modeling using the data of the average monthly electricity consumption for 226 apartments in ABs and for individual residential buildings in Chelyabinsk
according to the proposed approach
the average daily electric load on days during the month varies in the range of 2-3.5 kW/sq and below a
for the cities of Dushanbe and Khorog of the Republic of Tajikistan in the range of 2-5 kW/sq and below
which does not exceed the SEL of the given RB 256.1325800.2016. However
due to the lack of other energy sources (gas supply and hot water supply) in the conditions of the Republic of Tajikistan and on the basis of the obtained maximum load time factor and the generalized coefficient Ai(E)the obtained values of actual capacity exceed the maximum in hours by 1.2-2.5 times the SEL given RB 256.1325800.2016.