About Forecasting Accident Rate of Overhead Lines Main Grid Power System
Keywords:
overhead lines, failure flow parameter, deterministic chaos, fractal, Lyapunov exponent, forecasting
Abstract
The accident rate of overhead lines (OHL) of 500 kV of a large region over an extended time period was investigated. Significant fluctuations in the values of their failure flow parameter (failure frequency) were revealed. The indicated parameter was analyzed using the mathematical apparatus of the theory of deterministic (dynamic) chaos. An insignificant depth of forecasting the characteristics of the overhead line reliability due to the chaotic of the dynamic process under consideration is substantiated. This is an unfavorable factor that reduces the reliability of the power systems main grid.
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#
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15. STO 56947007–29.240.01.053–2010. Metodicheskiye ukazaniya po provedeniyu periodicheskogo tekhnicheskogo osvidetel’stvovaniya vozdushnykh liniy elektroperedachi YENES (STO 56947007–29.240.01.053–2010. Guidelines for the periodic technical survey of overhead power lines of the UNEG) [Electron. Resourse] URL: https://www.fsk?ees.ru/upload/docs/sto_5694700?29.240.01.053?2010.pdf. (Data of apple 19.03.2020).
2. Скопинцев В.А. Качество электроэнергетических систем: надёжность, безопасность, экономичность, живучесть. М.: Энергоатомиздат, 2009, 332 с.
3. Андриевский Б.Р., Фрадков А.Л. Управление хаосом: методы и приложения. I. Методы. – Автоматика и телемеханика, 2003, № 5, с. 3–54.
4. Андриевский Б.Р., Фрадков А.Л. Управление хаосом: методы и приложения. II. Приложения. – Автоматика и телемеханика, 2004, № 4, с. 3–34.
5. Higuchi T. Approach to an Irregular Time Series on the Basis of Fractal Theory. – Physica D., 1988, No. 31, pp. 277–283.
6. Higuchi T. Relationship between the Fractal Dimension and the Power?low Index for a Time Series: a Numerical Investigation. – Physica D., 1990, No. 46, pр. 254–264.
7. Flores!Marquez E.L., Galvez!Coyt G., Cifuentes!Nava G. Fractal dimension analysis of the magnetic time series associated with the volcanic activity of Popocatepetl. – Nonlinear Processes Geophysics, 2012, No.19, pp. 693–701.
8. Wolf A. Determining Lyapunov Exponent Form a Time Series. – Physica D., 1986, No.16, pp. 285–317.
9. Lei M., Wang Z., Feng Z. A method of embedding dimension estimation based on symplectic geometry. – Physics Letters, 2002, No. A303, p. 179–189.
10. Воеводин В.В., Кузнецов Ю.А. Матрицы и вычисления. М.: Наука, 1984, 320 с.
11. Мисриханов М.Ш., Рябченко В.Н. Квадратическая проблема собственных значений в электроэнергетических системах. – Автоматика и телемеханика, 2006, № 5, с. 24–47.
12. Лоскутов А.Ю., Михайлов А.С. Основы теории сложных систем. М.: Ижевск: Институт компьютерных исследований, 2007, 620 с.
13. Главные компоненты временных рядов: метод «Гусеница». Сб. статей/Ред.: Д.Л. Данилов, А.А. Жиглявский. Изд. Санкт-Петербургского университета, 1997, 308 с.
14. Леонтьева Л.Н. Многомерная гусеница, выбор длины и числа компонент. – Машинное обучение и анализ данных, 2011, №1, с. 2–10.
15. СТО 56947007–29.240.01.053–2010. Методические указания по проведению периодического технического освидетельствования воздушных линий электропередачи ЕНЭС [Электрон. ресурс]. URL: https://www.fsk?ees.ru/upload/docs/sto_5694700?29.240.01.053?2010.pdf. (дата обращения 19.03.2020).
#
1. Galiaskarov I.M., Misrikhanov M.Sh., Ryabchenko V.N., Shuntov A.V. Elektrichestvo – in Russ. (Electricity), 2019, No. 11, pp. 4—11.
2. Skopintsev V.A. Kachestvo elektroenergeticheskikh sistem: nadozhnost’, bezopasnost’, ekonomichnost’, zhivuchest’ (The quality of electric power systems: reliability, safety, efficiency, survivability). M.: Energoatomizdat, 2009, 332 p.
3. Andriyevskiy B.R., Fradkov A.L. Avtomatika i telemekhanika – in Russ. (Automation and Telemechanics), 2003, No. 5, p. 3–54.
4. Andriyevskiy B.R., Fradkov A.L. Avtomatika i telemekhanika – in Russ. (Automation and Telemechanics), 2004, №. 4, pp. 3–34.
5. Higuchi T. Approach to an Irregular Time Series on the Basis of Fractal Theory. – Physica D., 1988, No. 31, pp. 277–283.
6. Higuchi T. Relationship between the Fractal Dimension and the Power?low Index for a Time Series: a Numerical Investigation. – Physica D., 1990, No. 46, pр. 254–264.
7. Flores?Marquez E.L., Galvez?Coyt G., Cifuentes?Nava G. Fractal dimension analysis of the magnetic time series associated with the volcanic activity of Popocatepetl. – Nonlinear Processes Geophysics, 2012, No. 19, pp. 693–701.
8. Wolf A. Determining Lyapunov Exponent Form a Time Series. – Physica D., 1986, No.16, pp. 285–317.
9. Lei M., Wang Z., Feng Z. A method of embedding dimension estimation based on symplectic geometry. – Physics Letters, 2002, No. A303, p. 179–189.
10. Voyevodin V.V., Kuznetsov Yu.A. Matritsy i vychisleniya (Matrices and calculations). M.: Nauka, 1984, 320 p.
11. Misrikhanov M.Sh., Ryabchenko V.N. Avtomatika i telemekhanika – in Russ. (Automation and Telemechanics), 2006, No. 5, pp. 24–47.
12. Loskutov A.Yu., Mikhaylov A.S. Osnovy teorii slozhnykh system (Fundamentals of the theory of complex systems). Izhevsk: Institut komp’yuternykh issledovaniy, 2007, 620 p.
13. Glavnyye komponenty vremennykh ryadov: metod «Gusenitsa». Sb. statey (The main components of the time series: the Caterpillar method. Sat Articles) / Ed. D.L. Danilov, A.A. Zhiglyavsky. Publ. of St. Perrsburg University, 1997, 308 p.
14. Leont’yeva L.N. Mashinnoye obucheniye i analiz dannykh – in Russ. (Machine Learning and Data Analysis), 2011, No. 1, pp. 2–10.
15. STO 56947007–29.240.01.053–2010. Metodicheskiye ukazaniya po provedeniyu periodicheskogo tekhnicheskogo osvidetel’stvovaniya vozdushnykh liniy elektroperedachi YENES (STO 56947007–29.240.01.053–2010. Guidelines for the periodic technical survey of overhead power lines of the UNEG) [Electron. Resourse] URL: https://www.fsk?ees.ru/upload/docs/sto_5694700?29.240.01.053?2010.pdf. (Data of apple 19.03.2020).
