Analysis and Modeling of Protection System Hidden Failures and Its Impact on Power System Cascading Events

  • Diptak Pal
  • Balimidi MallikarjunaEmail author
  • M. Jaya Bharata Reddy
  • D. K. Mohanta


In this paper, a detailed study of the modes of hidden failures (HFs) in protection systems is carried out, and probabilistic modeling methodology is used for analyzing the impact of HFs on the power system cascading events. Further, the probabilistic model of HFs based on impedance and line power flow is hypothesized for qualitative evaluation of HF’s impact on power system cascading disruptions. Numerous case studies have been carried out on the IEEE-118 bus system to assess the effect of HFs by fitting the probability model of line outage based on impedance and power flow. This analysis has successfully identified the most sensitive transmission lines in the network which are having the highest tendency to trip in case of protective system HFs. Also, it has been shown that the probability of major blackouts will be reduced to a more significant extent if the self-checking and monitoring features are incorporated into digital relays. The qualitative analysis of protection system HFs could be helpful in planning, service and maintenance scheduling of a power system as well as determining the locations where an investment warrants the protection system reliability.


Protection system Hidden failures (HF) Probabilistic models Protection system reliability Power system cascading events 



  1. Aghamohammadi, M. R., & Salimian, M. R. (2018). A three stages decision tree based intelligent blackout predictor for power systems using brittleness indices. IEEE Transactions on Smart Grid, 9(5), 5123–5131.CrossRefGoogle Scholar
  2. Albinali, H. F., & Meliopoulos, A. P. (2017). Hidden failure detection via dynamic state estimation in substation protection systems. In Saudi Arabia Smart Grid (SASG), Jeddah (pp. 1–6).Google Scholar
  3. Bae, K., & Thorp, J. S. (1999). A stochastic study of hidden failures in power system protection. Decision Support Systems, 24(3/4), 259–268.CrossRefGoogle Scholar
  4. Chen, J., Thorp, J., & Dobson, I. (2005). Cascading dynamics and mitigation assessment in power system disturbances via a hidden failure model. International Journal of Electrical Power Energy System, 27(4), 318–326.CrossRefGoogle Scholar
  5. Dobson, I., Chen, J., Thorp, J. S., Carreras, B. A., & Newman, D. E. (2002). Examining criticality of blackouts in power system models with cascading events. In Proceedings of the 35th annual Hawaii international conference on system sciences, Big Island, HI (pp. 1–10).Google Scholar
  6. Final Report on the August 14. (2003). Blackout in the United States and Canada: Causes and Recommendations. April 2014.
  7. Gao, X., Thorp, J. S., & Hou, D. (2013). Case studies: Designing protection systems that minimize potential hidden failures. In 66th annual conference for protective relay engineers, College Station, TX (pp. 384-393).Google Scholar
  8. Henneaux, P. (2015). Probability of failure of overloaded lines in cascading failures. International Journal of Electrical Power Energy System, 73(141–148), 2015.Google Scholar
  9. Horowitz, S. H., Phadke, A. G., & Thorp, J. S. (1995). The role of adaptive protection in mitigating system blackouts. In 1995 CIGRE SC 34 colloquium, Stockholm (pp. 11–17).Google Scholar
  10. Hui, R., Xiaozhou, F., Watts, D., & Xingchen, L. (2012). Early warning mechanism for power system large cascading failures. In IEEE international conference on power system technology (POWERCON), Auckland (pp. 1–6).Google Scholar
  11. Jiao, Z., Gong, H., & Wang, Y. (2018). A D–S evidence theory-based relay protection system hidden failures detection method in smart grid. IEEE Transactions on Smart Grid, 9(3), 2118–2126.CrossRefGoogle Scholar
  12. Lai, L. L., Zhang, H., Tian, L., Chun Sing, X., Fang, Y., & Mishra, S. (2013). Investigation on July 2012 Indian blackout. In 2013 international conference on machine learning and cybernetics, Tianjin (pp. 92–97).Google Scholar
  13. Li, C., Sun, Y., & Chen, X. (2007). Analysis of the blackout in Europe on November 4, 2006. In International power engineering conference (IPEC 2007), Singapore (pp. 939–944).Google Scholar
  14. MATLAB and Statistics Toolbox Release. (2014a). The Math Works, Inc., Natick, MA.
  15. NERC. (1988). NERC Disturbance reports 1984–1988. North American Electric Reliability Council, New Jersey.Google Scholar
  16. Qi, H., & Shi, L., Sun, Q., & Yao, L. (2016). Risk assessment of cascading failures based on entropy weight method. In IEEE power and energy society general meeting (PESGM), Boston, MA (pp. 1–5).Google Scholar
  17. Report on Grid Disturbance on 30th July 2012 and Grid Disturbance on 31st July 2012 (2012, August).
  18. Seyedi, H., & Sanaye-Pasand, M. (2009). New centralised adaptive load-shedding algorithms to mitigate power system blackouts. IET Generation, Transmission and Distribution, 3(1), 99–114.CrossRefGoogle Scholar
  19. Sun, Q., Shi, L., Ni, Y., Si, D., & Zhu, J. (2017). An enhanced cascading failure model integrating data mining technique. Protection and Control of Modern Power Systems, 1(1), 1–10.Google Scholar
  20. Tamronglak, S., Phadke, A. G., Horowitz, S. H., & Thorp, J. S. (1996). Anatomy of power system blackouts: Preventive relaying strategies. IEEE Transactions on Power Delivery, 11(2), 708–715.CrossRefGoogle Scholar
  21. Thorp, J. S., Phadke, A. G., Horowitz, S. H., & Tamronglak, S. (1998). Anatomy of power system disturbances: Importance sampling. International Journal of Electrical Power & Energy, 20(2), 147–152.CrossRefGoogle Scholar
  22. Wang, X. F., & Xu, J. (2004). Cascading failures in coupled map lattices. Physical Review E, 70(1–5), 056113.CrossRefGoogle Scholar
  23. Wu, J. J., Gao, Z. Y., & Sun, H. J. (2006). Cascade and breakdown in scale-free networks with community structure. Physical Review E, 74(1–5), 066111.CrossRefGoogle Scholar
  24. Zhao, L., Li, X., Ni, M., Li, T., & Cheng, Y. (2015). Review and prospect of hidden failure: Protection system and security and stability control system. Journal of Modern Power System and Clean Energy. Scholar

Copyright information

© Brazilian Society for Automatics--SBA 2019

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringNational Institute of TechnologyTiruchirappalliIndia
  2. 2.Department of Electrical and Electronics EngineeringBirlal Institute of TechnologyMesraIndia

Personalised recommendations