Relationship between high voltage insulators incidents and climatic factors in AC Algerian electrical networks using ARDL approach

Relationship between high voltage insulators incidents and climatic factors in AC Algerian electrical networks using ARDL approach

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

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(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 Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The climatic factors have a strong influence on the polluted high voltage (HV) insulators performance and affect the reliability of networks. Such factors can lead to insulation incidents and outages in the electrical network. Based on monthly 12 weather factors observations (the average temperature, the precipitation, the humidity, the solar radiation, the vapour pressure, the snow depth, the dew point, the air pressure, the visibility, the total cloud cover, the wind direction and the wind speed) obtained during the period 2010–2015 (72 months) at Algerian central region, the authors propose an optimal relationship between the number of HV insulators incidents and the climatic factors. The autoregressive distributed lag (ARDL) method was employed to explore the actual and/or delayed (lagged) effect of each climatic factor on HV insulators performance. According to the results, the ARDL approach revealed the existence of strong relationship between these climatic variables and HV insulators incident. Also, the used statistical tests in this study allow us to say whether the proposed model is real and not simply due to chance. The proposed model has been validated by comparing the number of HV insulators incidents predicted for 10 months to real data recorded in Algerian AC transmission networks.


    1. 1)
      • 1. Farzaneh, M., Chisholm, W.A.: ‘Insulators for icing and polluted environments’ (John Wiley & Sons, New Jersey, USA, 2009, 1st edn.), p. 706.
    2. 2)
      • 2. Deng, Y., Jia, Z., Zhou, J., et al: ‘Ice flashover performance and its characterization parameter of composite insulator with booster sheds’, IEEE Trans. Dielectr. Electr. Insul., 2016, 23, (2), pp. 10211029.
    3. 3)
      • 3. Prasad, D.S., Reddy, B.S.: ‘Impact of mist and acidic fog on polymer insulator samples exposed to corona discharges’, IEEE Trans. Dielectr. Electr. Insul., 2016, 23, (3), pp. 15461554.
    4. 4)
      • 4. Terrab, H., El-Hag, A., Bayadi, A.: ‘Surface condition assessment of ceramic outdoor insulators under simulated pollution conditions’, Insight Non-Destruct. Test. Cond. Monit., 2016, 58, (9), pp. 502509.
    5. 5)
      • 5. Li, L., Li, Y., Lu, M., et al: ‘Quantification and comparison of insulator pollution characteristics based on normality of relative contamination values’, IEEE Trans. Dielectr. Electr. Insul., 2016, 23, (2), pp. 965973.
    6. 6)
      • 6. Douar, M.A., Beroual, A., Souche, X.: ‘Assessment of the resistance to tracking of polymers in clean and salt fogs due to flashover arcs and partial discharges degrading conditions on one insulator model’, IET Gener. Transm. Distrib., 2016, 10, (4), pp. 986994.
    7. 7)
      • 7. Wang, J., Xiong, X., Zhou, N., et al: ‘Time-varying failure rate simulation model of transmission lines and its application in power system risk assessment considering seasonal alternating meteorological disasters’, IET Gener. Transm. Distrib., 2016, 10, (7), pp. 15821588.
    8. 8)
      • 8. Wu, Y., Gao, C., Tang, Y., et al: ‘An outage risk oriented dynamic distribution network reconfiguration methodology considering the effects of weather conditions on power line failure rate’, Electr. Power Compon. Syst., 2016, 44, (19), pp. 22242236.
    9. 9)
      • 9. Hu, Q., Wang, S., Yang, H., et al: ‘Effects of icing degree on ice growth characteristics and flashover performance of 220kV composite insulators’, Cold Regions Sci. Technol., 2016, 128, pp. 4756.
    10. 10)
      • 10. Hu, Q., Wang, S., Shu, L., et al: ‘Comparison of AC icing flashover performances of 220 kV composite insulators with different shed configurations’, IEEE Trans. Dielectr. Electr. Insul., 2016, 23, (2), pp. 9951004.
    11. 11)
      • 11. Liu, Y., Du, B., Farzaneh, M.: ‘Characteristics of induced discharge on a polymer insulator surface under electro-wetting conditions’, IEEE Trans. Dielectr. Electr. Insul., 2015, 22, (5), pp. 29582967.
    12. 12)
      • 12. Sierra, R.C., Oviedo-Trespalacios, O., Candelo, J.E., et al: ‘Assessment of the risk of failure of high voltage substations due to environmental conditions and pollution on insulators’, Environ. Sci. Pollut. Res., 2015, 22, (13), pp. 97499758.
    13. 13)
      • 13. Palangar, M.F., Mirzaie, M.: ‘Detection of critical conditions in ceramic insulators based on harmonic analysis of leakage current’, Electr. Power Compon. Syst., 2016, 44, (16), pp. 18541864.
    14. 14)
      • 14. He, B., Jin, H., Gao, N., et al: ‘Characteristics of dust deposition on suspended insulators during simulated sandstorm’, IEEE Trans. Dielectr. Electr. Insul., 2010, 17, (1), pp. 100105.
    15. 15)
      • 15. Huang, X., Xie, C., Li, H.: ‘Equivalent salt deposit density optical fiber sensor for transmission lines in power grid’, IEEE Sens. J., 2016, 17, (1), pp. 9199.
    16. 16)
      • 16. Li, J., Sun, C., Sima, W., et al: ‘Contamination level prediction of insulators based on the characteristics of leakage current’, IEEE Trans. Power Deliv., 2010, 25, (1), pp. 417424.
    17. 17)
      • 17. Werneck, M.M., dos Santos, D.M., de Carvalho, C.C., et al: ‘Detection and monitoring of leakage currents in power transmission insulators’, IEEE Sens. J., 2015, 15, (3), pp. 13381346.
    18. 18)
      • 18. Zhao, S., Jiang, X., Xie, Y.: ‘Evaluating the contamination level of polluted insulators based on the characteristics of leakage current’, Int. Trans. Electr. Energy Syst., 2015, 25, (10), pp. 21092123.
    19. 19)
      • 19. Pesaran, M.H., Shin, Y., Smith, R.J.: ‘Bounds testing approaches to the analysis of level relationships’, J. Appl. Econ., 2001, 16, (3), pp. 289326.
    20. 20)
      • 20. Pesaran, M.H., Shin, Y.: ‘An autoregressive distributed-lag modelling approach to cointegration analysis’, Econ. Soc. Monogr., 1998, 31, pp. 371413.
    21. 21)
      • 21. McKinnish, T.G.: ‘Interpreting lagged effects of the independent variable: how does the local economy affect welfare caseloads?’, Terra, 2002, 303, pp. 4926770.
    22. 22)
      • 22. Dickey, D.A., Fuller, W.A.: ‘Likelihood ratio statistics for autoregressive time series with a unit root’, Econometrica, 1981, 49, (4), pp. 10571072.
    23. 23)
      • 23. Phillips, P.C., Perron, P.: ‘Testing for a unit root in time series regression’, Biometrika, 1988, 75, (2), pp. 335346.
    24. 24)
      • 24. Akaike, H.: ‘Akaike's information criterion’, in Lovric, M. (Ed.): ‘International encyclopedia of statistical science’ (Springer, Berlin, Germany, 2011), p. 25.
    25. 25)
      • 25. Zamani Mehreyan, S., Sayyareh, A.: ‘Separated hypotheses testing for autoregressive models with non-negative residuals’, J. Stat. Comput. Simul., 2017, 87, (4), pp. 689711.
    26. 26)
      • 26. Li, Y., Wolfs, P.J.: ‘Taxonomic description for western Australian distribution medium-voltage and low-voltage feeders’, IET Gener. Transm. Distrib., 2014, 8, (1), pp. 104113.
    27. 27)
      • 27. Zitouni, M., Guerbas, F., Boukezzi, L., et al: ‘Modelling by design of experiments method of the AC breakdown voltage of transformer oil point–plane gaps with insulating barrier’, IET Gener. Transm. Distrib., 2016, 10, (1), pp. 232239.
    28. 28)
      • 28. Li, X., Wang, K., Mu, W.: ‘Research on SID-IIs Rib characteristic based on DOE’. Proc. Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011, Harbin, China, pp. 34823484.
    29. 29)
      • 29. Lo, K., Wu, Y.: ‘Analysis of relationships between hourly electricity price and load in deregulated real-time power markets’, IEE Proc. Gener. Transm. Distrib., 2004, 151, (4), pp. 441452.
    30. 30)
      • 30. Forbes, C., Evans, M., Hastings, N., et al: ‘Chi-squared distribution’, In: ‘Statistical distributions’, (John Wiley & Sons, New Jersey, USA, 2010, 4th edn.), pp. 6973.
    31. 31)
      • 31. Breusch, T.S., Pagan, A.R.: ‘A simple test for heteroscedasticity and random coefficient variation’, Econometrica, 1979, 47, (5), pp. 12871294.
    32. 32)
      • 32. MacKinnon, J.G.: ‘Numerical distribution functions for unit root and cointegration tests’, J. Appl. Econ., 1996, pp. 601618.
    33. 33)
      • 33. Hogg, R.V., McKean, J., Craig, A.T.: ‘Introduction to Mathematical Statistics’, (Pearson Education, Boston, USA, 2012, 7th edn.), p. 640.
    34. 34)
      • 34. Vogelvang, B.: ‘Econometrics: theory and applications with Eviews’ (Pearson Education, Harlow, England, UK, 2005, 1st edn.), p. 126.
    35. 35)
      • 35. Bourbonnais, R.: ‘Econométrie - Cours et exercices corrigés’ (Dunod, Paris, France, 2015, 9é edn.), p. 81.
    36. 36)
      • 36. Wilson, E.B., Hilferty, M.M.: ‘The distribution of chi-square’, Proc. Natl. Acad. Sci., 1931, 17, (12), pp. 684688.
    37. 37)
      • 37. Engle, R.F.: ‘Wald, likelihood ratio, and Lagrange multiplier tests in econometrics’, in Griliches, Z., Intriligator, M.D. (Eds.): ‘Handbook of econometrics’, (Elsevier Science Publishers BV, Amsterdam, Netherlands, 1984), vol. 2 (1984), pp. 775826.

Related content

This is a required field
Please enter a valid email address