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Application of Statistical Methods in the Organization of Selective Control of the Quality Indicators of Electric Energy in the Power Supply Networks of Industrial Enterprises

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Power Technology and Engineering Aims and scope

Integrating renewable energy and diverse active consumers into distribution networks causes electric power quality indicators (EPQI) to deviate from their standard values. In the industrial setting, production lines and distributed generation facilities adopted are susceptible to voltage dips and interruptions to non-sinusoidal voltage and current, which means that EPQIs at the ownership demarcation point must remain at any network operating mode to be maintained. For this purpose, industrial facilities implement systems for continuous or selective monitoring of EPQIs. This paper demonstrates the effectiveness of using statistical methods in EPQI monitoring systems for selective control of EPQIs and a quantitative characteristic with exponentially distributed deviations in specific indicators. It further presents the algorithm of the developed quantitative characteristic-based EPQI analyzer, which obtains data from the EPQI monitoring system equipped with EPQI control instrumentation. Calculations showed that Wald’s sequential analysis is effective for selective EPQI monitoring and can triple the performance of decision-making algorithms that compute deviations in certain parameters compared to a fixed sample. A generated database of simulation modeling and tracking of the current operating modes of the network ensures adaptation of the monitoring process and selective control of EPQI to the needs of the specific facility’s internal power supply network.

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References

  1. V. E. Vorotnitsky, “Energy saving and energy efficiency improvement in electrical distribution networks of a new technological order,” Élektroénerg. Pered. Raspred., No. 4(67), 88 – 96 (2021).

  2. B. V. Papkov, A. L. Kulikov, Issues of the Market Electric Power Industry [in Russian], VVAGS, Nizhny Novgorod (2005).

    Google Scholar 

  3. E. Vorotnitsky, Yu. A. Dementiev, G. B. Lazarev, and Yu. G. Shakaryan, “Organization of an integrated process of power quality management as a priority task of the energy development strategy of Russia,” Élektroénerg. Pered. Raspred., No. 4(43), 40 – 52 (2017).

  4. P. V. Ilyushin, O. A. Sukhanov, “The structure of emergencymanagement systems of distribution networks in large cities,” Russ. Electr. Eng., 85(3), 133 – 137 (2014). DOI: https://doi.org/10.3103/S1068371214030067

    Article  Google Scholar 

  5. I. I. Kartashev, V. N. Tulsky, Power Quality Management [in Russian], Izd. MÉI, Moscow (2006).

    Google Scholar 

  6. G. Ya. Vagin, A. L. Kulikov, “The quality of electrical energy in power supply systems. Analysis of the state of regulation and control methods,” Élektr. Stantsii, No. 6(1055), 54 – 59 (2019).

  7. A. L. Kulikov, M. V. Sharygin and P. V. Ilyushin, “Principles of organization of relay protection in microgrids with distributed power generation sources,” Power Technol. Eng., 53(5), 611 – 617 (2020). DOI: https://doi.org/10.1007/s10749-020-01125-x

    Article  Google Scholar 

  8. P. V. Ilyushin, “Analysis of the specifics of selecting relay protection and automatic (RPA) equipment in distributed networks with auxiliary low-power generating facilities,” Power Technol. Eng., 51(6), 713 – 718 (2018). DOI: https://doi.org/10.1007/s10749-018-0898-0

    Article  Google Scholar 

  9. D. J. Won, I. Y. Chung, J. M. Kim, S. J. Ahn, and S. I. Moon, “A modified voltage SAG duration for power quality diagnosis,” Proc. IFAC, 36(20), 739 – 743 (2003). DOI: https://doi.org/10.1016/s1474-6670(17)34559-7

    Article  Google Scholar 

  10. J.Won, S. J. Ahn, and S. I. Moon, “A modified sag characterization using voltage tolerance curve for power quality diagnosis,” IEEE Trans. Power Deliv., 20(4), 2638 – 2643 (2005). DOI: https://doi.org/10.1109/tpwrd.2005.855626

    Article  Google Scholar 

  11. K. Lacommare, J. Eto, “Cost of Power Interruptions to Electricity Consumers in the United States (US),” Energy, 31(12), 1845 – 1855 (2006). DOI: https://doi.org/10.1016/j.energy.2006.02.008

    Article  Google Scholar 

  12. P. V. Ilyushin, A. L. Kulikov, “Characteristics of the implementation of automatic control of power district modes with distribution generation facilities,” Rel. Zashch. Avtom., No. 3(36), 14 – 23 (2019).

  13. P. V. Ilyushin, A. L. Kulikov, K. V. Suslov, and S. P. Filippov, “Consideration of distinguishing design characteristics of gasturbine and gas-reciprocating units in design of emergency control systems,” Machines, 9(3), 47 (2021). DOI: https://doi.org/10.3390/machines9030047

    Article  Google Scholar 

  14. M. H. J. Bollen, P. M. E. Dirix, “Simple model for post-fault motor behavior for reliability/power quality assessment of industrial power systems,” IEEE Proc. Gen. Transm. Distrib., 143(1), 56 – 60 (1996). DOI: https://doi.org/10.1049/ip-gtd:19960047

    Article  Google Scholar 

  15. P. F. Ribeiro, C. A. Duque, P. M. da Silveira, and A. S. Cerqueira, Signal Processing in Intelligent Networks of Power Systems, Tekhnosfera, Moscow (2020).

  16. V. A. Falshina, A. L. Kulikov, “Algorithms for simplified digital filtration of electrical signals of industrial frequency,” Prom. Énerget., No. 5, 39 – 46 (2012).

  17. D. Cowden, Statistical Methods of Quality Control [Russian translation], Fizmatgiz, Moscow (1961).

    Google Scholar 

  18. V. S. Mkhitaryan, Statistical Methods in Product Quality Management [in Russian], Finansy i statistika, Moscow (1982).

    Google Scholar 

  19. Ya. B. Shor, Statistical Methods of Analysis and Quality Control and Reliability [in Russian], Sovetskoye radio, Moscow (1962).

    MATH  Google Scholar 

  20. L. Knowler et al., Statistical Methods of Product Quality Control [Russian translation], Izd. standartov, Moscow (1989).

    Google Scholar 

  21. GOST 32144–2013. Electrical Energy. Electromagnetic Compatibility of Technical Means. Standards for the Quality of Electrical Energy in General-Purpose Power Supply Systems [in Russian], Standartinform, Moscow (2014).

  22. GOST 16504–81. Testing and Product Quality Control. Basic Terms and Definitions [in Russian], Standartinform, Moscow (2011).

  23. A. Wald, Sequential Analysis [in Russian], Fizmatlit, Moscow (1960).

    MATH  Google Scholar 

  24. GOST R 50779.76–2018 (ISO 39511:2018). Statistical Methods. Procedures for Selective Control on a Quantitative Basis. Sequential Control Plans for the Percentage of Nonconforming Items (Known Standard Deviation) [in Russian], Standartinform, Moscow (2018).

  25. Yu. K. Belyaev, Probabilistic Methods of Selective Control [in Russian], Nauka, Moscow (1975).

    Google Scholar 

  26. GOST R 50779.50–95. Statistical Methods. Acceptance Quality Control on a Quantitative Characteristic Basis. General Requirements [in Russian], Gosstandart Rossii, Moscow (1995).

  27. GOST R 50779.12–2021. Statistical Methods. Statistical Quality Control. Methods for Random Selection of Samples of Piece Products [in Russian], Standartinform, Moscow (2021).

  28. V. B. Goryainov, I. V. Pavlov, G.M. Tsvetkova et al., Mathematical Statistics. Textbook for Universities [in Russian], Izd. MGTU im. N. É. Baumana, Moscow (2001).

  29. GOST 33073–2014. Electrical Energy. Electromagnetic Compatibility of Technical Means. Control and Monitoring of the Quality of Electrical Energy in General-Purpose Power Supply Systems [in Russian], Standartinform, Moscow (2015).

  30. A. N. Shiryaev, Statistical Sequential Analysis. Optimal Termination Rules [in Russian], Fizmatlit, Moscow (1976).

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Authors and Affiliations

  1. R. E. Alekseev Nizhny Novgorod State Technical University, Nizhny Novgorod, Russia

    A. L. Kulikov & P. V. Ilyushin

  2. Energy Research Institute of the Russian Academy of Sciences (ERI RAS), Moscow, Russia

    A. A. Sevostyanov

Authors
  1. A. L. Kulikov
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  2. P. V. Ilyushin
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  3. A. A. Sevostyanov
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Correspondence to P. V. Ilyushin.

Additional information

Translated from Élektricheskie Stantsii, No. 12, December 2021, pp. 28 – 37. DOI: https://doi.org/10.34831/EP.2021.1085.12.004

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Kulikov, A.L., Ilyushin, P.V. & Sevostyanov, A.A. Application of Statistical Methods in the Organization of Selective Control of the Quality Indicators of Electric Energy in the Power Supply Networks of Industrial Enterprises. Power Technol Eng 56, 137–145 (2022). https://doi.org/10.1007/s10749-023-01485-0

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  • DOI: https://doi.org/10.1007/s10749-023-01485-0

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