Estimation of switching surge flashover rate of point on wave switching over-voltages along transmission line by adaptive neuro-fuzzy inference system meta-model

Estimation of switching surge flashover rate of point on wave switching over-voltages along transmission line by adaptive neuro-fuzzy inference system meta-model

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Science, Measurement & Technology — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Limiting switching overvoltages (SOVs) and performing proper insulation coordination against stresses caused by them have great importance in UHV transmission lines (TLs). The point on wave switching (PWS) is the best strategy to limit SOV without needing any arrester. Although detailed electromagnetic transient studies are carried out in the design of transmission systems, such studies are not common in day-to-day operations. However, it is important for the power utility and/or operator to ensure that the peak value of SOVs is well within the safe limits. This study presents a new PWS strategy in the EMTP/ATP environment by considering line-trapped charge to train an adaptive neuro-fuzzy inference system meta-model used to estimate the SOVs and to determine spots of critical failure risk caused by SOVs along TLs. The proposed meta-model can be used by power utilities and/or design engineers for planning the proper insulation level without consuming time to meet a desirable value of risk. Moreover, the operators can decide on the energisation of lines in sequence, which is safe and leads to successful energisation. In order to reduce the training error, an intelligent method based on two-stage data classification is introduced in which k-means clustering method is used.


    1. 1)
      • 1. Shariatinasab, R., Ghayur Safar, J., Falaghi, H.: ‘Optimisation of arrester location in risk assessment in distribution network’, IET Gener. Transm. Distrib., 2014, 8, (1), pp. 151159.
    2. 2)
      • 2. Akafi-Mobarakeh, M.: ‘Estimation of switching overvoltages on transmission lines using fuzzy method’. M.S. thesis, Electrical Engineering, Power Systems, Faculty of Engineering, The University of Birjand, Iran, 2012.
    3. 3)
      • 3. Thukaram, D., Khincha, H.P., Khandelwal, S.: ‘Estimation of switching transient peak overvoltages during transmission line energization using artificial neural network’, Electr. Power Sys. Res., 2006, 76, (4), pp. 259269.
    4. 4)
      • 4. Taher, S.A., Sadeghkhani, I.: ‘Estimation of magnitude and time duration of temporary overvoltages using ANN in transmission lines during power system restoration’, Simul. Model. Pract. Theory, 2010, 18, (6), pp. 787805.
    5. 5)
      • 5. Shariatinasab, R., Vahidi, B., Hosseinian, S.H., et al: ‘Optimization of surge arrester's location on EHV and UHV power networks using simulation optimization method’, IEEJ Trans. Power Energy, 2008, 128, (12), pp. 18.
    6. 6)
      • 6. Seyedi, H., Tanhaeidilmaghani, S.: ‘New controlled switching approach for limitation of transmission line switching overvoltages’, IET Gener. Transm. Distrib., 2013, 7, (3), pp. 218225.
    7. 7)
      • 7. Atefi, M.A., Sanaye-Pasand, M.: ‘Improving controlled closing to reduce transients in HV transmission lines and circuit breakers’, IEEE Trans. Power Deliv., 2013, 2, (7), pp. 733741.
    8. 8)
      • 8. Sanaye-Pasand, M., Dadashzadeh, M. R., Khodayar, M.: ‘Limitation of transmission line switching overvoltages using switchsync relays’. Proc. Int. Conf. Power System Transients, Canada, 2005, pp. 16.
    9. 9)
      • 9. Wei, L., Chun-en, F., Bi-de, Z., et al: ‘Research on controlled switching in reducing unloaded power transformer inrush current considering circuit breaker's prestrike characteristics’. Int. Symp. Discharges and Electrical Insulation in Vacuum, Suzhou, China, 2016.
    10. 10)
      • 10. Rocha, R., Tavora, J.L.: ‘EMTP model for controlled switching simulation by means of TACS routine’. Int. Conf. Power Systems Transients (IPST), Seattle, USA, 1997, pp. 254259.
    11. 11)
      • 11. Bhatt, K.A., Bhalja, B.R., Parikh, U.: ‘Controlled switching technique for minimization of switching surge during energization of uncompensated and shunt compensated transmission lines for circuit breakers having pre-insertion resistors’, Int. J. Electr. Power Energy Syst., 2018, 103, pp. 347359.
    12. 12)
      • 12. Lin, D., Wang, H., Lin, D., et al: ‘An adaptive reclosure scheme for parallel transmission lines with shunt reactors’, IEEE Trans. Power Deliv., 2015, 30, (6), pp. 25812589.
    13. 13)
      • 13. Mestas, P., Tavares, M.C., Gole, A.M.: ‘Implementation and performance evaluation of a reclosing method for shunt reactor-compensated transmission lines’, IEEE Trans. Power Deliv., 2011, 26, (2), pp. 954962.
    14. 14)
      • 14. Dantas, K.M.C., Neves, W.L.A., Fernandes, D.: ‘An approach for controlled reclosing of shunt-compensated transmission lines’, IEEE Trans. Power Deliv., 2014, 29, (3), pp. 12031211.
    15. 15)
      • 15. Shariatinasab, R., Vahidi, B., Hosseinian, S.H., et al: ‘Probabilistic evaluation of the optimal location of surge arresters on EHV and UHV networks due to switching and lightning surges’, IEEE Trans. Power Deliv., 2009, 24, (4), pp. 19031911.
    16. 16)
      • 16. ATP-EMTP Rule Book, Canadian-American EMTP Users Group, 1997.
    17. 17)
      • 17. Akafi Mobarakeh, M., Shariatinasab, R.: ‘Implementing Switch-Sinc. Relay in the EMTP/ATP and evaluation of insulation risk’. Int. Power System Conf. (ICEE), Tehran, Iran, 2013, pp. 16.
    18. 18)
      • 18. Hosseinian, S., Abedi, M., Vahidi, B.: ‘Digital computer studies of random switching of Iranian standard 400 kV lines’. Proc. of the 3rd Int. Conf. on Properties and Applications of Dielectric Materials, Tokyo, Japan, 1991, pp. 542545.
    19. 19)
      • 19. Martinez, J.A., Durbak, D.W.: ‘Parameter determination for modeling systems transients—part V: surge arresters’, IEEE Trans. Power Deliv., 2005, 20, (3), pp. 20732078.
    20. 20)
      • 20. Cigre Working Group: ‘Switching overvoltages in EHV and UHV systems with special reference to closing and reclosing transmission lines’, Electra, 1973, 30, pp. 70122.
    21. 21)
      • 21. Akafi Mobarakeh, M., Shariatinasab, R.: ‘Evaluation of switching overvoltage and cost of failure with considering altitude profile’. Iranian Student Conf. on Electrical Engineering, Kashan, 2012, pp. 16.
    22. 22)
      • 22. Prikler, L., Hoidalen, H.K.: ‘ATPDRAW, version 5.6, for windows 9x/NT/2000/XP/vista’, User's Manual, 2009.
    23. 23)
      • 23. Dantas, K.M.C., Neves, W.L.A., Fernandes, D.Jr., et al: ‘On applying controlled switching to transmission lines: case studies’. Int. Conf. on Power Systems Transients (IPST), Tokyo, Japan, 2009, pp. 16.
    24. 24)
      • 24. Anane, Z., Bayadi, A.: ‘Studies on the influence of corona on overvoltage surges by simulation using the ATP/EMTP’. Int. Conf. on Microelectronics (ICM), Algiers, Algeria, 2012, pp. 14.
    25. 25)
      • 25. Cervantes, M., Kocar, I., Montenegro, A., et al: ‘Simulation of switching overvoltages and validation with field tests’, IEEE Trans. Power Deliv., 2018, 33, (6), pp. 28842893.
    26. 26)
      • 26. Hosseinian, S.H.: ‘Determining the probability density of switching the high voltage cable by EMTP software’. 8th Electric Power Distribution Conf. (EPDC), Iran, 2003, pp. 19.
    27. 27)
      • 27. Keokhoungning, T., Premrudeeprechacharn, S., Ngamsanroaj, K.: ‘Switching overvoltage analysis of 500 kV transmission line between Nam Theun 2 and Roi Et 2’. Int. Conf. on Asia-Pacific Power and Energy Engineering, Tokyo, Japan, 2009, pp. 16.
    28. 28)
      • 28. IEC publicaion 71.1: ‘Insulation coordination part1 definitions, principles and rules’, 1993.
    29. 29)
      • 29. Hileman, A.R.: ‘Insulation coordination for power systems’ (Marcel Dekker, New York, 1999).
    30. 30)
      • 30. Shariatinasab, R., Vahidi, B., Hosseinian, S.H.: ‘Statistical evaluation of lightning-related failures for the optimal location of surge arresters on the power networks’, IET Gener. Transm. Distrib., 2009, 3, (2), pp. 129144.
    31. 31)
      • 31. Reddy, M., Mohanta, D.K.: ‘Performance evaluation of an adaptive-network-based fuzzy inference system approach for location of faults on transmission lines using Monte Carlo simulation’, IEEE Trans. Fuzzy Syst., 2008, 16, (4), pp. 909919.
    32. 32)
      • 32. Qingbo, Z., Yuanbing, Z., Rong, G., et al: ‘Application of fuzzy neural network in power system marginal price forecasting’, Power Syst. Technol., 2004, 28, (7), pp. 4548.
    33. 33)
      • 33. Shariatinasab, R., Ghayur safar, J., Akafi-Mobarakeh, M.: ‘Development of an adaptive neural-fuzzy inference system based meta-model for estimating lightning related failures in polluted environments’, IET Sci. Meas. Technol., 2014, 8, (4), pp. 187195.
    34. 34)
      • 34. Shariatinasab, R., Akafi Mobarakeh, M., Farshad, M.: ‘Estimation of switching overvoltages on transmission lines using neuro-fuzzy method’, Intell. Syst. Electr. Eng., 2013, 3, (3), pp. 5566.
    35. 35)
      • 35. Mora, J.J., Carrillo, G., Perez, L.: ‘Fault location in power distribution systems using ANFIS nets and current patterns’. Proc. IEEE PES Transmission and Distribution Conf. Exposition Latin America, Caracas, Venezuela, August 2006, pp. 16.

Related content

This is a required field
Please enter a valid email address