Statistical evaluation of lightning-related failures for the optimal location of surge arresters on the power networks

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Statistical evaluation of lightning-related failures for the optimal location of surge arresters on the power networks

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Direct lightning strokes cause unscheduled supply interruptions in power systems because of a failure of the insulation. Metal oxide surge arresters, as a proper protective device, have been widely adopted in power systems to reduce lightning initiated flashovers and, hence, increase the power quality and reliability of the systems. Based on a genetic algorithm approach, a cost effective solution is described to find the optimum location of surge arresters on a power network in order to minimise the global risk of the network, and to improve its reliability. A statistical approach to evaluate lightning failures has been introduced and an optimisation procedure developed to analyse the network in order to satisfy the power utility requirement for a specific value of risk and/or line performance with a minimum set of arresters, that is, at minimum cost. Not only the insulation flashover but also the failure of the arrester can affect the reliability of power systems. Therefore, both the failure of the insulation and that of the arrester are considered in the proposed method.

Inspec keywords: lightning protection; arresters; power system reliability; power system faults; flashover; statistics; genetic algorithms

Other keywords: surge arresters; power supply interruptions; direct lightning strokes; flashover protection; statistical evaluation; insulation flashover; power system reliability; genetic algorithm; lightning-related failures; power networks

Subjects: Other topics in statistics; Optimisation techniques; Reliability; Protection apparatus

References

    1. 1)
    2. 2)
    3. 3)
      • K. Nakada , T. Yokota , S. Yokoyama , A. Asakawa . Energy absorption of surge arresters on distribution lines due to direct lightning strokes – effect of an overhead ground wire and installation position of surge arrester. IEEE Trans. Power Deliv. , 4 , 1779 - 1785
    4. 4)
      • G.J. Anders . (1990) Probability concepts in electric power systems.
    5. 5)
    6. 6)
    7. 7)
      • A.R. Hileman . (1999) Insulation coordination for power systems.
    8. 8)
      • D.E. Goldberg . (1989) Genetic algorithm in search, optimization and machine learning.
    9. 9)
      • P. Chowdhuri . (1996) Electromagnetic transients in power systems.
    10. 10)
      • Estimation lightning performance of transmission lines II: update to analytical models. IEEE Trans. Power Deliv. , 3 , 1245 - 1267
    11. 11)
      • R.C. Bansal . Optimization methods for electric power systems: an overview. Int. J. Emerging Electr. Power Syst. , 1 , 1 - 23
    12. 12)
      • IEC Std. 71-2: ‘Insulation coordination – Part 2: application guide’, 1996.
    13. 13)
      • A.O. Fernandez , S.B. Bogarra , M.A. Grau Gotes . Optimization of surge arrester's location. IEEE Trans. Power Deliv. , 1 , 145 - 150
    14. 14)
      • (1982) Transmission line reference book, 345 kV and above.
    15. 15)
      • Tarasiewicz, E.J.: `Lightning performance of transmission surge arresters on 115 kV transmission line', IWD, CIGRE SC33-95.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • CIGRE WG 33-01.: ‘Guide to procedures for estimating the lightning performance of transmission lines’. CIGRE Brochure 63, 1991.
    20. 20)
      • L. Chambers . (2001) The practical handbook of genetic algorithms applications.
    21. 21)
      • Ghafuri, A.R.: `Investigation transmission line outages of Iranian national grid', Internal Report of the Iran Power Generation, Transmission and Distribution Management Company, 2004, 2, p. 24–29.
    22. 22)
      • Modeling of metal oxide surge arresters. IEEE Trans. Power Deliv. , 1 , 302 - 309
    23. 23)
    24. 24)
      • A. Greenwood . (1991) Electrical transients in power systems.
    25. 25)
    26. 26)
      • Parameters of lightning strokes: a review. IEEE Trans. Power Deliv. , 1 , 346 - 358
    27. 27)
      • R. Billinton , R.N. Allan . (1983) Reliability evaluation of engineering systems: concepts and techniques.
    28. 28)
      • V. Miranda , J.V. Ranito , L.V. Proenca . Genetic algorithms in optimal multistage distribution systems. IEEE Trans. Power Deliv. , 4 , 1927 - 1933
    29. 29)
      • Modeling guidelines for fast transients. IEEE Trans. Power Deliv. , 1 , 493 - 506
    30. 30)
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