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KPI Science News
ISSN 2617-5509 · e‑ISSN 2663-7472 Open Access · CC BY 4.0
Vol. · Issue 2 · 2021 Aug 31, 2021 article

DETERMINATION OF “WEAK” BY POWER TRANSFORMERS RELIABILITY OF POWER SYSTEMS ACCORDING TO THE RESULTS OF FAILURE RISK ASSESSMENT UNDER EXTERNAL SHORT CIRCUITS

EB
Eugeniy I. Bardik Corresponding Igor Sikorsky Kyiv Polytechnic Institute, Ukraine Ukraine
MB
Mykola P. Bolotniy Igor Sikorsky Kyiv Polytechnic Institute, Ukraine Ukraine
YK
Yaroslav S. Koval Igor Sikorsky Kyiv Polytechnic Institute, Ukraine Ukraine
PublishedAug 31, 2021
KPISN 2 VOL · 2
VOL · ISS 2 · 2021 View issue

Abstract

Background. The increase of technological violation intensity and its consequences severity is caused mainly by objectively existing aging and service life depletion of electrical equipment. The power industry liberalization exacerbates the reliable operation problem of the power system and requires identification of power system operation accompanied by the maximum emergency risk with possible cascade accidents development. Therefore, the model development task for assessment of the equipment failure risk based on the diagnostic results of technical condition in particular under short circuit in the external network is relevant today. Objective. The aim of the work is to develop a fuzzy mathematical model for probability assessment of power transformer failure in the presence of a windings defect, short circuit in external network and emergency risk assessment under power transformers out of service. Methods. The fuzzy set theory and fuzzy logic were used for developing a mathematical model of risk assessment of power trans- former failure. The problems of determining the “weak” in terms of power transformers reliability of power systems based on the results of failure risk assessment due to external short circuits were solved by methods of fuzzy logic and probabilistic-statistical simulation of electric power system modes. Results. The necessity of complex simulation of electric power system modes is substantiated for probability assessment of power transformer failure under electrical network disturbances. The simulation of technical condition of power transformer windings was carried out. The short circuit influence on operability level of power transformers of electric power system was investigated. The quantitative indicators of operational risk of electric power system were determined under power transformers out of service. Conclusions. The linguistic mathematical model for estimating the failure probability of power transformer windings in the presence of defect and short circuit in electrical network has been developed to determine the quantitative indicators of emergency risk in power system.

Keywords

References

  1. J. Silva et al., “The challenges of estimating the impact of distributed energy resources flexibility on the TSO/DSO boundary node operating points,” Comput. Operat. Res., vol. 96, pp. 294–304, 2018. doi: 10.1016/j.cor.2017.06.004
  2. M.V. Kosterev et al., “Preventive risk-management of power system for its reliability increasing,” WSEAS TRANS. POWER SYST., vol. 10. pp. 251–258, 2015.
  3. H.H. Alhelou et al., “A Survey on power system blackout and cascading events: Research motivations and challenges,” Energies, vol. 12, no. 4, pp. 1–28, 2019. doi: 10.3390/en12040682
  4. Y. Shiwen et al., “Review on risk assessment of power system,” Procedia Comput. Sci., vol. 109, pp. 1200–1205, 2017. doi: 10.1016/j.procs.2017.05.399
  5. M.V. Kosterev et al., The issue of constructing fuzzy models for assessing the technical state of objects of electrical systems. Кyiv, Ukraine: NTUU KPI, 2011. 148 p.
  6. R.M.A. Velasquez and J.V.M. Lara, “Expert system for power transformer diagnosis,” in 2017 IEEE XXIV Int. Conf. on Electronics, Electrical Engineering and Computing, Cusco, Peru, 15-18 August 2017, 2017. doi: 10.1109/intercon.2017.8079640
  7. D. Lin et al., “A risk assessment method of transformer considering the economy and reliability of power network,” in 2017 1st Int. Conf. on Electrical Materials and Power Equipment (ICEMPE), Xi'an, China, 14-17 May 2017. doi: 10.1109/icempe.2017.7982167
  8. A.M. Leite da Silva et al., “Transmission expansion planning: A discussion on reliability and “N−1” security criteria,” in 2010 IEEE 11th Int. Conf. on Probabilistic Methods Applied to Power Systems, Singapore, 14-17 June 2010. doi: 10.1109/pmaps.2010.5528652
  9. E. Handschin et al., “Long term optimization for risk-oriented asset management,” in 16th Power Systems Computation Conf., Glasgow, Scotland, 2008.
  10. S.A.V. Goerdin et al., “Monte Carlo simulation applied to support risk-based decision making in electricity distribution networks,” in 2015 IEEE Eindhoven PowerTech, Eindhoven, Netherlands, 29 June-2 July 2015 2015.
  11. doi: 10.1109/ptc.2015.7232494
  12. E. Duarte et al., “A practical approach to condition and risk based power transformer asset replacement,” in 2010 IEEE Int. Symp. on Electrical Insulation, San Diego, CA, USA, 6-9 June 2010. doi: 10.1109/elinsl.2010.5549580
  13. B. Wang et al., “A new MOPSO to solve a multi-objective portfolio selection model with fuzzy value-at-risk,” in Knowledge-Based and Intelligent Information and Engineering Systems, Berlin, Heidelberg: Springer, 2011, pp. 217–226.
  14. doi: 10.1007/978-3-642-23854-3_23
  15. H. Yang et al., “A novel method of decision-making for power transformer maintenance based on failure-probability-analysis,” IEEJ Trans. Elect. Electron. Eng., vol. 13, no. 5, p. 689–695, 2018. doi: 10.1002/tee.22618
  16. E. Bardyk and N. Bolotnyi, “Parametric identification of fuzzy model for power transformer based on real operation data,” Eastern-European J. Enterprise Technol., vol. 6, no. 8 (90), pp. 4–10, 2017. doi: 10.15587/1729-4061.2017.118632
  17. T. L. Saaty, “Decision making with the analytic hierarchy process,” Int. J. Services Sci., vol. 1, no. 1, pp. 83–98, 2008. doi: 10.1504/IJSSCI.2008.017590
  18. E.I. Bardyk, “Modelling and assessment of chances of failure of power systems electrical equipment taking into account the after repair resource restoration level,” Sci. Bulletin National Mining University, no. 3, pp. 82–90, 2014.
  19. E.I., Bardyk and N.P. Bolotnyi, “Electric power system simulation for risk assessment of power transformer failure under external short-circuit conditions,” in 2017 IEEE First Ukraine Conf. Electrical and Computer Engineering (UKRCON), Kyiv, Ukraine, 29 May-2 June 2017. doi: 10.1109/ukrcon.2017.8100527
  20. E.I. Bardyk, “Models of reliability assessing of electricity supply of auxiliary NPP from external sources with fuzzy defined parameters of failures of equipments,” Proc. Institute of Electrodynamics of National Academy of Sciences of Ukraine, Kyiv, Ukraine, 2014, pp. 34–38.
  21. E. Bardyk and N. Bolotnyi, “Development of a mathematical model for cost distribution of maintenance and repair of electrical equipment,” Eastern-European J. Enterprise Technol., vol. 6, no. 8 (96), pp. 6–16, 2018. doi: 10.15587/1729-4061.2018.147622
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