Accounting the factor of randomity of social processes in prediction of demand for electric energy

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Authors:


D.V.Yatsenko, orcid.org/0000-0001-6702-569X, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.A.Popov, orcid.org/0000-0003-3484-4597, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.P.Rozen, orcid.org/0000-0002-0440-4251, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.I.Zamulko, orcid.org/0000-0001-8018-6332, National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

O.V.Adanikov, orcid.org/0000-0003-2773-244X, TapOk IT-company, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


повний текст / full article



Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2022, (2): 067 - 072

https://doi.org/10.33271/nvngu/2022-2/067



Abstract:



Purpose.
Taking into account the factor of randomness of social processes when forecasting the demand for electric energy to reduce the error.


Methodology.
Apparatus of mathematical statistics, linear programming methods, fuzzy set theory and expert assessment methods, scale theory, Bayesian approach to forecasting models, computer modeling.


Findings.
The dynamics of consumption of electric energy for different periods of time is analyzed, the influence of the pandemic factor on the process of formation of demand for electric energy is established. A verbal-numerical scale has been developed for a comprehensive assessment of the impact on the demand for electric energy of such a complex social phenomenon as a pandemic. A model for forecasting the demand for electrical energy was formed using the Bayesian approach and an experts assessment, which made it possible to use retrospective data on electrical energy consumption and take into account the uncertainty of the social factor influencing the pandemic.


Originality.
The model for forecasting the demand for electrical energy has been further developed, which, unlike others, takes into account the factor of randomness of social processes and a verbal-numerical scale, which makes it possible to reduce the error in predicting the consumption of electrical energy.


Practical value.
The research results are useful for enterprises specializing in the generation, transmission and distribution of electrical energy to consumers. The presented results make it possible to reduce the error in forecasting the demand for electric energy, taking into account the factor of randomness of social processes.



Keywords:
demand for electricity, forecasting, uncertainty, power system, Bayesian method, Covid-19, expert judgment

References.


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