Resilience of Electrical Distribution Systems with Critical Load Prioritization

  • Zejun Yang
  • Jose R. MartiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10707)


In the highly interdependent environment of a large city, failures in the electrical distribution system can cause direct or indirect consequences to other critical infrastructures and to the Human Well-being Level (HWL) of the citizens. This paper discusses the electrical distribution system in terms of how topological reconfiguration, together with prioritized system recovery can maintain a high level of Human Well-being resilience during system failures. The Infrastructure Interdependencies Simulator (i2SIM) is used to prioritize load restoration and load shedding algorithms. To validate the proposed approach, spanning tree search algorithms, load shedding schemes and optimization methods are applied to find optimal restoration strategies on a standard IEEE 30-node system and on a 70-node distribution system with critical loads.


Electrical distribution system restoration i2SIM Human Well-being Level Smart city resilience Load shedding Spanning tree algorithms 


  1. 1.
    Martí, J.R., Ghahremani, E., Martí, A.: The GDW index: an extension of the GDP index to include human well-being. Eur. CIIP Newsl. 10(2), 23–26 (2016)Google Scholar
  2. 2.
    Hokstad, P.: Risk and Interdependencies in Critical Infrastructures A Guideline for Analysis, pp. 67–79. Springer, London (2012). Scholar
  3. 3.
    Veremyeva, A., Sorokin, A., Boginski, V., Pasiliao, E.L.: Minimum vertex cover problem for coupled interdependent networks with cascading failures. Eur. J. Oper. Res. 232(3), 499–511 (2014)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Rahnamay-Naeini, M., Hayat, M.M.: Cascading failures in interdependent infrastructures: an interdependent Markov-chain approach. IEEE Trans. Smart Grid 7(4), 1997–2006 (2016)CrossRefGoogle Scholar
  5. 5.
    Khushalani, S., Solanki, J.M., Schulz, N.N.: Optimized restoration of unbalanced distribution systems. IEEE Trans. Power Syst. 22(2), 624–630 (2007)CrossRefGoogle Scholar
  6. 6.
    Romero, R., Franco, J.F., Leão, F.B., Rider, M.J., de Souza, E.S.: A new mathematical model for the restoration problem in balanced radial distribution systems. IEEE Trans. Power Syst. 31(2), 1259–1268 (2016)CrossRefGoogle Scholar
  7. 7.
    Liu, C.-C., Lee, S.-J., Venkata, S.S.: An expert system operational aid for restoration and loss reduction of distribution systems. IEEE Trans. Power Syst. 3(2), 619–626 (1988)CrossRefGoogle Scholar
  8. 8.
    D’Agostino, F., Silvestro, F., Schneider, K.P., Liu, C.-C., Xu, Y., Ton, D.T.: Reliability assessment of distribution systems incorporating feeder restoration actions. In: Power Systems Computation Conference (PSCC), Genoa, pp. 1–7 (2016)Google Scholar
  9. 9.
    Li, J., Ma, X.Y., Liu, C.C., Schneider, K.P.: Distribution system restoration with microgrids using spanning tree search. IEEE Trans. Power Syst. 29(6), 3021–3029 (2014)CrossRefGoogle Scholar
  10. 10.
    Alsubaie, A.: Improving critical infrastructure resilience with application to power distribution networks. University of British Columbia. Accessed (2016).
  11. 11.
    Gao, H., Chen, Y., Yin, X., Liu, C.-C.: Resilience-oriented critical load restoration using microgrids in distribution systems. IEEE Trans. Smart Grid 7, 2837–2848 (2016)CrossRefGoogle Scholar
  12. 12.
    Ahmadi, H., Alsubaie, A., Martí, J.R.: Distribution system restoration considering critical infrastructures interdependencies. In: IEEE PES General Meeting—Conference & Exposition, pp. 1–5 (2014)Google Scholar
  13. 13.
    Bie, Z., Lin, Y., Li, G., Li, F.: Battling the extreme: a study on the power system resilience. In: Proceedings of the IEEE, vol. PP, no. 99, pp. 1–14 (2017)Google Scholar
  14. 14.
    D’Agostino, G., et al.: Methodologies for inter-dependency assessment. In: 5th International Conference on Critical Infrastructure (CRIS), Beijing, pp. 1–7 (2010)Google Scholar
  15. 15.
    Fioriti, V., D’Agostino, G., Bologna, S.: On modeling and measuring inter-dependencies among critical infrastructures. In: 2010 Complexity in Engineering, pp. 85–87, Rome (2010)Google Scholar
  16. 16.
    Martí, José R.: Multisystem simulation: analysis of critical infrastructures for disaster response. In: D’Agostino, G., Scala, A. (eds.) Networks of Networks: The Last Frontier of Complexity. UCS, pp. 255–277. Springer, Cham (2014). Scholar
  17. 17.
    Brown, R.E.: Electric Power Distribution Reliability. CRC Press, Boca Raton (2008)CrossRefGoogle Scholar
  18. 18.
    Graham, R.L., Hell, P.: On the history of the minimum spanning tree problem. Ann. Hist. Comput. 7(1), 43–57 (1985)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Sheng, Y., Qin, Z., Shi, G.: Minimum spanning tree problem of uncertain random network. J. Intell. Manuf. 1–10 (2014)Google Scholar
  20. 20.
    Verayiah, R., Ramasamy, A., Abidin, H.I.Z., Musirin, I.: Under voltage load shedding (UVLS) study for 746 test bus system. In: 3rd International Conference on Energy and Environment (ICEE), pp. 98–103, Malacca (2009)Google Scholar
  21. 21.
    Meier, R., Cotilla-Sánchez, E., Fern, A.: A policy switching approach to consolidating load shedding and Islanding protection schemes. In: 2014 Power Systems Computation Conference, pp. 1–7, Wroclaw (2014)Google Scholar
  22. 22.
    Verayiah, R., Ramasamy, A., Abidin, H.I.Z., Musirin, I.: Under voltage load shedding (UVLS) study for 746 test bus system. In: 2009 3rd International Conference on Energy and Environment (ICEE), pp. 98–103, Malacca (2009)Google Scholar
  23. 23.
    Safdarian, A., Farajollahi, M., Fotuhi-Firuzabad, M.: Impacts of remote control switch malfunction on distribution system reliability. IEEE Trans. Power Syst. 32(2), 1572–1573 (2017)Google Scholar
  24. 24.
    Yusof, N.A., Mokhlis, H., Karimi, M., Laghari, J.A., Illias, H.A., Sapori, N.M.: Under-voltage load shedding scheme based on voltage stability index for distribution network. In: 3rd IET International Conference on Clean Energy and Technology (CEAT), pp. 1–5, Kuching (2014)Google Scholar
  25. 25.
    Cormen, M.L.A., Thomas, H., et al.: Greedy Algorithms. Introduction to Algorithms 1, pp. 329–355 (2001)Google Scholar
  26. 26.
    Hokstad, P.: Risk and Interdependencies in Critical Infrastructures: A Guideline for Analysis, pp. 67–79. Springer, Heidelberg (2012). Scholar
  27. 27.
    Baran, M.E., Wu, F.F.: Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans. Power Deliv. 4(2), 1401–1407 (1989)CrossRefGoogle Scholar
  28. 28.
    Das, D.: A fuzzy multiobjective approach for network reconfiguration of distribution systems. IEEE Trans. Power Deliv. 21(1), 202–209 (2006)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.The University of British ColumbiaVancouverCanada

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