Smart Electromechanical Systems in Electric Power Engineering: Concept, Technical Realization, Prospects

  • Aleksandr N. ShilinEmail author
  • Aleksey A. Shilin
  • Sergey S. Dementiev
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 174)


Problem statement: Reducing the accident rate of overhead power lines (OHL) is one of the priority areas for the development of the electrical power industry. The reliability of overhead power lines depends on a large number of various factors, among which, it is necessary to highlight extreme climatic loads, leading to frequent failures of OHL due to wire breakage. Prompt recognition of emergency line mode, fault localization, and isolation of the damaged area network are the basis for the prompt restoration of power supply. To successfully solve this problem, it is proposed to use a “smart” electromechanical system (SEMS), namely, it is a switching device mounted on the OHL tower and combined with a neurocomputer information processing unit. The neurocomputer, based on processing of information from sensors of current, voltage and meteorological parameters, and in the event of an accident, controls the switching of power lines. The difference between SEMS and a conventional vacuum switch with an electric drive with a constant setpoint is the automatic correction of the setpoint value, which depends on external factors. The purpose of the research: The development of an algorithm for functioning of a circuit breaker with a neurocomputer, ensuring a reliable operation of the circuit breaker to isolate the damaged section of the OHL. Results: The concept of SEMS is proposed in the form of an information-measuring and control system combined with a vacuum switching device and assuming the use of an information processing unit based on an artificial neural network. Practical significance: Modern switching devices implemented with a rigid logic and a constant setpoint value don’t possess the ability of adaptation with the environmental conditions. The proposed smart electromechanical system lacks this disadvantage due to the use of a neurocomputer, which allows taking into account the location of the switching device, the time of year and external climatic factors. The introduction of SEMS as an element in the smart grid will allow to increase the reliability of power supply systems by reducing the time of recovery of accidents.


Reliability of power supply Accidents on OHL Fault location Smart electromechanical systems (SEMS) Artificial neural networks Smart grids 


  1. 1.
    Fardiev, A., et al.: Status and prospects for the development of energy. On the innovative project “smart grid. Energetics Tatarstan 3, 5–12 (2010)Google Scholar
  2. 2.
    Lachugin, V., et al.: Principles of constructing smart relay protection of electrical grids. Proc. Acad. Sci. Energetics 4, 28–37 (2015)Google Scholar
  3. 3.
    Bulychev, A., Navolochny, A.: Relay protection in distribution electrical grids; a manual for practical calculations. ENAS, Moscow (2011)Google Scholar
  4. 4.
    Margolin, N.: Resistance of Overhead Power Lines. United Scientific and Technical Publishing House, Moscow-Leningrad. The main edition of energy literature (1937)Google Scholar
  5. 5.
    Zarudsky, G.: Calculation of the temperature of wires of EHV transmission lines on the basis of the method of criterial experiment planning. Vestnik MEI 1, 85–90 (1997)Google Scholar
  6. 6.
    Dementiev, S.: Diagnosis of the state of overhead power lines with the use of a neurocomputer. Energy Resour Saving Ind. Transp. 2(19), 21–26 (2017)Google Scholar
  7. 7.
    Shilin, A., Shilin, A., Dementiev, S.: The use of artificial neural networks for forecasting accidents of overhead power lines during the ice-covered period. Electro. Electr. Eng. Electr. Power Ind. Electrotech. Ind. 2, 15–21 (2016)Google Scholar
  8. 8.
    Masters, T.: Practical neural network recipes in C++. Academic Press Inc, Boston (1993)zbMATHGoogle Scholar
  9. 9.
    Osovsky, S.: Neural networks for information processing. Finance and Statistics, Moscow (2002)Google Scholar
  10. 10.
    Osipov, O.: Technical diagnostics of automated electric drives. Energoatomizdat, Moscow (1991)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Aleksandr N. Shilin
    • 1
    Email author
  • Aleksey A. Shilin
    • 1
  • Sergey S. Dementiev
    • 1
  1. 1.Volgograd State Technical UniversityVolgogradRussia

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