Seismic loss assessment: the case study of the power distribution network in Arak city, Iran

Document Type : Original Article

Authors

1 Department of Civil Engineering, Faculty of Engineering, Arak University, P.O. Box 38156‐88359, Arak, Iran.

2 University of Strathclyde Department of Civil and Environmental Engineering James Weir Building 75 Montrose Street Glasgow G1 1XJ United Kingdom.

Abstract

Vital infrastructures have, nowadays, a high level of importance in urban areas. Any disruption in one of the infrastructures can cause severe impacts on inhabitants and consequently can affect the other infrastructure systems. In this regard, the electricity grid is considered to be one of the most critical infrastructures, and it has been performed vulnerable to natural hazards, specifically in past earthquakes. Iran is located in a high seismic activity region. Therefore, in this study, the seismic vulnerability of the power distribution network in Arak city has been comprehensively investigated. The power grid has three sections consisting: the electricity generation, transmission, and distribution. In this study, a seismic risk analysis was carried out on its distribution section. The obtained results show that the seismic hazard in the north-eastern part of Arak city is at the lowest level, and in the south-west region, it is at the highest level. Then, the potential damage to the network and the possible financial losses have been calculated. It was revealed that the 315 KVA transformer substations, 615 KVA transformer substations, and finally transmission lines, are at the highest seismic risk of financial damage. According to the obtained results, the probable financial losses for a return period of 475 years event for the 315 KVA transformer substations, the 615 KVA transformer substations, the transmission lines with 120 mm and 70 mm aluminum wires are, respectively, 22300000, 5717000, 270000, and 700000 U.S. dollars.

Keywords

Main Subjects

References

[1] Vanzi I. Seismic reliability of electric power networks: methodology and application. Structural Safety. 1996 Jan 1;18(4):311-27. [View at Google Scholar] ; [View at Publisher].
[2] Rose A, Benavides J, Chang SE, Szczesniak P, Lim D. The regional economic impact of an earthquake: direct and indirect effects of electricity lifeline disruptions. Journal of Regional Science. 1997 Aug;37(3):437-58. [View at Google Scholar] ; [View at Publisher].
[3] Shinozuka M, Dong X, Jin X, Cheng TC. Seismic performance analysis for the ladwp power system. In2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific 2005 Aug 18 (pp. 1-6). IEEE. [View at Google Scholar] ; [View at Publisher].
[4] Dueñas‐Osorio L, Craig JI, Goodno BJ. Seismic response of critical interdependent networks. Earthquake engineering & structural dynamics. 2007 Feb;36(2):285-306. [View at Google Scholar] ; [View at Publisher].
[5] Volkanovski A, Čepin M, Mavko B. Application of the fault tree analysis for assessment of power system reliability. Reliability Engineering & System Safety. 2009 Jun 1;94(6):1116-27. [View at Google Scholar] ; [View at Publisher].
[6] Chang L, Wu Z. Performance and reliability of electrical power grids under cascading failures. International Journal of Electrical Power & Energy Systems. 2011 Oct 1;33(8):1410-9. [View at Google Scholar] ; [View at Publisher].
[7] Giovinazzi S, Pollino M, Kongar I, Rossetto T, Caiaffa E, Di Pietro A, La Porta L, Rosato V, Tofani A. Towards a decision support tool for assessing, managing and mitigating seismic risk of electric power networks. InInternational Conference on Computational Science and Its Applications 2017 Jul 3 (pp. 399-414). Springer, Cham. [View at Google Scholar] ; [View at Publisher].
[8] Poulos A, Espinoza S, de la Llera JC, Rudnick H. Seismic risk assessment of spatially distributed electric power systems. In16th World Conf. on Earthquake Eng., Santiago 2017 Jan (pp. 1949-3029). [View at Google Scholar] ; [View at Publisher].
[9] Salman AM, Li Y. A probabilistic framework for multi-hazard risk mitigation for electric power transmission systems subjected to seismic and hurricane hazards. Structure and Infrastructure Engineering. 2018 Nov 2;14(11):1499-519. [View at Google Scholar] ; [View at Publisher].
[10] Wang C, Feng K, Zhang H, Li Q. Seismic performance assessment of electric power systems subjected to spatially correlated earthquake excitations. Structure and Infrastructure Engineering. 2019 Mar 4;15(3):351-61. [View at Google Scholar] ; [View at Publisher]
[11] Dunn S, Wilkinson S, Alderson D, Fowler H, Galasso C. Fragility curves for assessing the resilience of electricity networks constructed from an extensive fault database. Natural Hazards Review. 2018 Feb 1;19(1):04017019. [View at Google Scholar] ; [View at Publisher]
[12] Nazemi M, Moeini-Aghtaie M, Fotuhi-Firuzabad M, Dehghanian P. Energy storage planning for enhanced resilience of power distribution networks against earthquakes. IEEE Transactions on Sustainable Energy. 2019 Mar 26;11(2):795-806. [View at Google Scholar] ; [View at Publisher]
[13] Brennan AL, Koliou M. Probabilistic loss assessment of a seismic retrofit technique for medium-and high-voltage transformer bushing systems in high seismicity regions. Structure and Infrastructure Engineering. 2020 Jun 29:1-0. [View at Google Scholar] ; [View at Publisher]
[14] Farahani S, Tahershamsi A, Behnam B. Earthquake and post-earthquake vulnerability assessment of urban gas pipelines network. Natural Hazards. 2020 Feb 12:1-21. [View at Google Scholar] ; [View at Publisher]
[15] Liu Y, Wotherspoon L, Nair NK, Blake D. Quantifying the seismic risk for electric power distribution systems. Structure and Infrastructure Engineering. 2020 Mar 5:1-6. [View at Google Scholar] ; [View at Publisher]
[16] McGuire RK. Probabilistic seismic hazard analysis and design earthquakes: closing the loop. Bulletin of the Seismological Society of America. 1995 Oct 1;85(5):1275-84. [View at Google Scholar] ; [View at Publisher]
[17] Federal Emergency Management Agency and National Institute of Building Sciences (1999) Earthquake loss estimation methodology Hazus99—technical manual. [View at Publisher]
[18] Ordaz M, Aguilar A, Arboleda J. CRISIS2007. Program for computing seismic hazard. Instituto de Ingenierıa, Universidad Naconal Autónoma de México, UNAM, México. 2007. [View at Google Scholar] ; [View at Publisher]
[19] International Institute of Earthquake Engineering and Seismology: http://www.iiees.ac.ir/[View at Google Scholar] ; [View at Publisher].
[20] Scordilis EM. Empirical global relations converting M S and m b to moment magnitude. Journal of seismology. 2006 Apr 1;10(2):225-36. [View at Google Scholar] ; [View at Publisher].
[21] Gardner JK, Knopoff L. Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian?. Bulletin of the Seismological Society of America. 1974 Oct 1;64(5):1363-7. [View at Google Scholar] ; [View at Publisher].
[22] Gutenberg B, Richter CF. Frequency of earthquakes in California. Bulletin of the Seismological Society of America. 1944 Oct 1;34(4):185-8. [View at Google Scholar] ; [View at Publisher].
[23] Kijko A, Sellevoll MA. Estimation of earthquake hazard parameters from incomplete data files. Part II. Incorporation of magnitude heterogeneity. Bulletin of the Seismological Society of America. 1992 Feb 1;82(1):120-34. [View at Google Scholar] ; [View at Publisher].
[24] Atkinson GM, Goda K. Effects of Seismicity Models and New Ground-Motion Prediction Equations on Seismic Hazard Assessment for Four Canadian CitiesEffects of Seismicity Models and Ground-Motion Prediction Equations on Seismic Hazard Assessment. Bulletin of the Seismological Society of America. 2011 Feb 1;101(1):176-89. [View at Google Scholar] ; [View at Publisher]
[25] Stewart JP, Douglas J, Javanbarg M, Bozorgnia Y, Abrahamson NA, Boore DM, Campbell KW, Delavaud E, Erdik M, Stafford PJ. Selection of ground motion prediction equations for the global earthquake model. Earthquake Spectra. 2015 Feb;31(1):19-45. [View at Google Scholar] ; [View at Publisher]
[26] Toro G. The effects of ground-motion uncertainty on seismic hazard results: Examples and approximate results. InProc. of the Annual Meeting of the Seismological Society of America 2006 Apr. [View at Google Scholar] ; [View at Publisher]
[27] Boore DM, Stewart JP, Seyhan E, Atkinson GM. NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthquake Spectra. 2014 Aug;30(3):1057-85. [View at Google Scholar] ; [View at Publisher]
[28] Abrahamson NA, Silva WJ, Kamai R. Summary of the ASK14 ground motion relation for active crustal regions. Earthquake Spectra. 2014 Aug;30(3):1025-55. [View at Google Scholar] ; [View at Publisher]
[29] Chiou BS, Youngs RR. Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra. 2014 Aug;30(3):1117-53. [View at Google Scholar]
[30] Campbell KW, Bozorgnia Y. NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthquake Spectra. 2014 Aug;30(3):1087-115. [View at Google Scholar]
[31] Zafarani H, Soghrat M. Simulation of ground motion in the Zagros region of Iran using the specific barrier model and the stochastic method. Bulletin of the Seismological Society of America. 2012 Oct 1;102(5):2031-45. [View at Google Scholar] ; [View at Publisher]
Journal of Civil Engineering and Materials Application
Volume 4, Issue 4
December 2020
Pages 195-207

Files

History

  • Receive Date: 22 August 2020
  • Revise Date: 30 October 2020
  • Accept Date: 21 November 2020

Share

How to cite

Statistics