Analysis of modern approaches for the prediction of electric energy consumption

Kalimoldayev, M.; Drozdenko, Oleksii Oleksandrovych; Koplyk, Ihor Volodymyrovych; Marynych, Tetiana Oleksandrivna; Abdildayeva, А.; Zhukabayeva, T.

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Title	Analysis of modern approaches for the prediction of electric energy consumption
Authors	Kalimoldayev, M. Drozdenko, Oleksii Oleksandrovych Koplyk, Ihor Volodymyrovych Marynych, Tetiana Oleksandrivna Abdildayeva, А. Zhukabayeva, T.
ORCID	http://orcid.org/0000-0002-0047-739X http://orcid.org/0000-0003-2217-731X http://orcid.org/0000-0002-1393-7607
Keywords	prediction power consumption panel models autoregression models neural networks
Type	Article
Date of Issue	2020
URI	https://essuir.sumdu.edu.ua/handle/123456789/77555
Publisher	De Gruyter
License	Creative Commons Attribution - NonCommercial 4.0 International
Citation	Kalimoldayev, Maksat, Drozdenko, Aleksey, Koplyk, Igor, Marinich, T., Abdildayeva, Assel and Zhukabayeva, Tamara. "Analysis of modern approaches for the prediction of electric energy consumption" Open Engineering, vol. 10, no. 1, 2020, pp. 350-361. https://doi.org/10.1515/eng-2020-0028
Abstract	A review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches, as well as their applicability to the energy systems of Ukraine and Kazakhstan, are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed.
Appears in Collections:	Наукові видання (ЕлІТ)