Information technologies and computer sciences

Anomaly detection in the raw data electrical load of energy-intensive enterprises

Authors

P. O. Chernenko
Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
O. V. Martyniuk
Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
V. O. Miroshnyk
Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
A. I. Zaslavskyi
Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv

Keywords

достовіризація аномальні значення електричне навантаження енергоємні підприємства

Abstract

This paper presents the advantages and disadvantages of three methods for the identification and recovery of anomalous values of electric power load based on the methods of statistical time series analysis and mathematical apparatus of artificial neural networks. The effectiveness of the proposed anomaly detection algorithms has been tested on real data of electrical loads of energy-intensive enterprises of Dnipropetrovsk region.

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How to Cite

[1]
“Anomaly detection in the raw data electrical load of energy-intensive enterprises”, Вісник ВПІ, no. 2, pp. 84–91, Mar. 2015, Accessed: Oct. 07, 2026. Available: https://visnyk.vntu.edu.ua/index.php/visnyk/article/view/815

Author Biographies

P. O. Chernenko, Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
Dr. Sc. (Eng.), Professor, Senior Research Assistant of the Department of Modelling of Electrical Power Objects and Systems
O. V. Martyniuk, Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
Cand. Sc. (Eng.)., Senior Research Assistant of the Department of Modeling of Electrical Power Objects and Systems
V. O. Miroshnyk, Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
Post-Graduate Student of the Department of Modeling of Electrical Power Objects and Systems
A. I. Zaslavskyi, Institute of Electrodynamics of National Academy of Science of Ukraine, Kyiv
Leading Programming Engineer of the Department of Modeling of Electrical Power Objects and Systems

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