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.

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

References

1. Черненко П. О. Багаторівневе короткострокове прогнозування сумарного електричного навантаження енергооб’єднання
/ П. О. Черненко, О. В. Мартинюк // Вісник Вінницького політехнічного інституту, Вінниця — 2011. — № 2. С. 74—80.
2. Черненко П. А. Методы повышения достоверности телеизмеряемых параметров режима электроэнергетических сис-
тем / П. А. Черненко, А. И. Заславский // Електродинаміка : пр. Ін-ту електродинаміки НАНУ. — 2001. — С. 109—114.
3. Черненко П. А. Обработка и анализ информации для иерархического прогнозирования электрических нагрузок /
П. А. Черненко, А. И. Заславский, А. В. Мартынюк // Праці ІЕД НАНУ. — 2006. — Вип. 2(14). — С. 47—49.
4. Черненко П. О. Прогнозування добового графіка сумарного електричного навантаження електроенергетичної сис-
теми / П. О. Черненко, О. В. Мартинюк // Праці ІЕД НАНУ. — 2007. — Вип. 18. — С. 57—65.
5. Пустыльник Е. И. Статистические метолы анализа и обработки наблюдений / Е. И. Пустыльник. — М. : Наука,
1968. — 288 с.

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Published

2015-03-26

How to Cite

[1]
P. O. Chernenko, O. V. Martyniuk, V. O. Miroshnyk, and A. I. Zaslavskyi, “Anomaly detection in the raw data electrical load of energy-intensive enterprises”, Вісник ВПІ, no. 2, pp. 84–91, Mar. 2015.

Issue

No 2 (2015)

Section

Information technologies and computer sciences

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