Natural Hazards

, Volume 74, Issue 3, pp 1555–1575 | Cite as

On the modeling of ground-motion field for assessment of multiple-location hazard, damage, and loss: example of estimation of electric network performance during scenario earthquake

Original Paper
  • 249 Downloads

Abstract

Consideration of within-earthquake ground-motion correlation is essential for the estimation of seismic hazards, damage, and loss for spatially distributed systems. In many seismically active regions, the strong motion data of real engineering significance are completely unavailable or very scarce. The absence of necessary data does not allow developing regional empirical correlation models, and the models obtained for other regions should be used with correspondent sensitivity analysis. The level of within-earthquake correlation may vary in broad range; therefore, development of correspondent criteria for selection from available models is important. In this paper, we analyzed the performance of a system of critical elements of electric power network (substations) depending on variations in within-earthquake correlation. The performance is described as probability of different levels of non-functionality, i.e., percentage of area suffering power outage, and probability of expected number of customers without power. We have shown that the proper choice of the within-earthquake correlation model is critical in comprehensive estimations of functionality of substations in electrical power system. Skipping the ground-motion variability and within-earthquake correlation may lead to unreliable results. Relevance of geology-based within-earthquake correlation models has been demonstrated, and a scheme, which allows reducing uncertainty in the choice of realistic correlation, has been proposed.

Keywords

Within-earthquake correlation models Functionality of electric system Substations Scenario earthquakes 

References

  1. Abrahamson N, Atkinson G, Boore D, Bozorgnia Y, Campbell K, Chiou B, Idriss IM, Silva W, Youngs R (2008) Comparison of the NGA ground–motion relations. Earthq Spectra 24:45–66. doi:10.1193/1.2924363 CrossRefGoogle Scholar
  2. Adachi T, Ellingwood BR (2008) Serviceability of earthquake-damaged water systems: effect of electrical power availability and power backup systems on system vulnerability. Reliab Eng Syst Saf 93:78–88. doi:10.1016/j.ress.2006.10.014 CrossRefGoogle Scholar
  3. Anderson J, Hough S (1984) A model for the shape of the Fourier amplitude spectrum of acceleration at high frequencies. Bull Seismol Soc Am 74:1969–1993Google Scholar
  4. Ang AHS, Pires JA, Villaverde R (1996) A model for the seismic reliability assessment of electric power transmission systems. Reliab Eng Syst Saf 51:7–12. doi:10.1016/j.ress.2006.10.014 CrossRefGoogle Scholar
  5. Araneda JC, Rudnick H, Mocarquer S, Miguel P (2010) Lessons from the 2010 Chilean earthquake and its impact on electricity supply. In: International conference on power system technology (Powercom 2010), Hanzhou, China, October 24–28Google Scholar
  6. Azevedo J, Guirreiro L, Bento R, Lopes M, Proenca J (2004) Seismic impact on lifelines in the Great Lisbon area. In: 13 world conference on earthquake engineering, Vancouver, BC Canada, August 1–6, 2004, paper 489Google Scholar
  7. Bastami M, Takada S, Kuwata Y (2006) Methodology and application of flow path analysis of lifeline network systems. In: First European conference on earthquake engineering and seismology, Geneva, Switzerland, 3–8 September, paper 466Google Scholar
  8. Brune JN (1970) Tectonic stress and the spectra of seismic shear waves from earthquakes. J Geophys Res 75:4997–5009CrossRefGoogle Scholar
  9. Brune JN (1971) Correction. J Geophys Res 76:5002CrossRefGoogle Scholar
  10. Brüstle W, Stange S (1999) Geologische Untergrundklassen zum Entwurf von Normspektren für DIN 4149 (neu). Landesamt für Geologie, Rohstoffe und Bergbau Baden-Württemberg Freiburg i. BrGoogle Scholar
  11. Cagnan Z, Davidson R (2004) Post earthquake restoration modeling of electric power systems. In: 13th world conference on earthquake engineering, Vancouver, BC, Canada, August 1–6, paper 109Google Scholar
  12. Chang SE, Pason C, Yavari S, Elwood K (2009) Social impacts of lifeline losses: modeling displaced populations and health care functionality. In: Tang AKK, Werner S (eds) Proceedings of the 2009 technical council on lifeline earthquake engineering (TCLEE) conference: lifeline earthquake engineering in a multihazard environment, Oakland, June 28–July 1, 2009. ASCE, Reston, VA, ISBN: 978-0-7844-1050-9, 1514 pp. doi:10.1061/41050(357)54
  13. Crowley H, Bommer JJ, Stafford PJ (2008) Recent developments in the treatment of ground–motion variability in earthquake loss model. J Earthq Eng 12(S2):71–80. doi:10.1080/13632460802013529 CrossRefGoogle Scholar
  14. Dowell LJ, Maheshwari S (2000) Simulating earthquake damage to the electric-power infrastructure: a case study for urban planning and policy development. Los Alamos National Laboratory Technical Report LA-UR-00-3777, Los Alamos, NM, 25 ppGoogle Scholar
  15. Du W, Wang W (2013) Intra-event spatial correlations for cumulative absolute velocity, arias intensity, and spectral accelerations based on regional site conditions. Bull Seismol Soc Am 103:1117–1129. doi:10.1785/0120120185 CrossRefGoogle Scholar
  16. Dueñas-Osorio L, Kwasinski A (2012) Quantification of lifeline system interdependencies after the 27 February 2010 Mw 8.8 offshore Maule, Chile earthquake. Earthq Spectra 28(S1):S581–S603CrossRefGoogle Scholar
  17. Dueñas-Osorio L, Craig JI, Goodno BJ (2007) Seismic response of critical interdependent networks. Earthq Eng Struct Dyn 36(2):285–306. doi:10.1002/eqe.626 CrossRefGoogle Scholar
  18. Eidinger J (2009) Wenchuan earthquake impact to power systems. In: Tang AKK, Werner S (eds) Proceedings of the 2009 technical council on lifeline earthquake engineering (TCLEE) conference: lifeline earthquake engineering in a multihazard environment, Oakland, June 28–July 1. ASCE, Reston, VA, ISBN: 978-0-7844-1050-9, 1514 pp. doi:10.1061/41050(357)128
  19. Esposito S, Iervolino I (2011) PGA and PGV spatial correlation models based on European multi-event databases. Bull Seismol Soc Am 101:2532–2541. doi:10.1785/0120110117 CrossRefGoogle Scholar
  20. FEMA (2003) HAZUS-MH MRS, technical manual. Federal Emergency Management Agency, Washington DCGoogle Scholar
  21. Giovinazzi S, King A (2009) Seismic performance of geographically distributed lifelines: an international overview. New Zealand Society of Earthquake Engineering Annual Conference (NZSEE), Christchurch, New Zealand, 3–5 April 2009. http://ir.canterbury.ac.nz/bitstream/10092/3667/1/12623491_NZSEE%202009%20-%20Giovinazzi%20%26%20King.pdf. (Last accessed 28 Mar 2013)
  22. Goda K, Hong HP (2008) Spatial correlation of peak ground motions and response spectra. Bull Seismol Soc Am 98:354–365. doi:10.1785/0120070078 CrossRefGoogle Scholar
  23. Gould NC, Ballantyne D (2005) The impact on lifelines on the estimation of natural hazard loss. Free risk management and multiline commentary, IRMI risk management and insurance library, http://www.irmi.com/expert/articles/2005/gould07.aspx. (Last accessed 28 Mar 2013)
  24. Hernández-Fajardo I, Dueñas-Osorio L (2013) Probabilistic study of cascading failures in complex interdependent lifeline systems. Reliab Eng Syst Saf 111:260–272CrossRefGoogle Scholar
  25. Jayaram N, Baker JW (2009) Correlation models for spatially distributed ground motion intensities. Earthq Eng Struct Dyn 38:1687–1708. doi:10.1002/eqe.922 CrossRefGoogle Scholar
  26. Jayaram N, Baker JW (2010) Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment. Earthq Eng Struct Dyn 39:1109–1131. doi:10.1002/eqe.988 Google Scholar
  27. J-POWER Group (2011) The effect of the Great East Japan earthquake and J-POWER Group’s responses. http://www.jpower.co.jp/english/company_info/environment/pdf/er2011pdf/11-05.pdf. (Last assessed 28 Mar 2013)
  28. Keintzel E (2005) About the way to the new German Seismic Code DIN 4149: 2005-04. Bautechnik 82(8):475–485 (in German with English summary)CrossRefGoogle Scholar
  29. Kempner L, Eidinger J, Perez J, Schiff A (2006) Seismic risk of a high voltage transmission network. In: Proceedings of the EERI 8th national conference on earthquake engineering, San Francisco, CD-ROM, 8NCEE-001485Google Scholar
  30. Khalvati AH, Hosseini M (2009) Seismic performance of electrical substations’ equipments in Bam Earthquake (Iran 2003). In: Tang AKK, Werner S (eds) Proceedings of the 2009 technical council on lifeline earthquake engineering (TCLEE) conference: lifeline earthquake engineering in a multihazard environment, Oakland, June 28–July 1. ASCE, Reston, VA, ISBN: 978-0-7844-1050-9, 1514 pp. doi:10.1061/41050(357)23
  31. Kuwata Y, Takada S (2007) Seismic risk assessment of lifeline considering hospital functions. Asian J Civ Eng (Build Hous) 8(3):315–328Google Scholar
  32. Liu GY, Liu CW, Wang YJ, Jean WY (2004) Seismic risk analysis of electric power network using hazard-consistent scenario earthquakes. In: 13th world conference on earthquake engineering, Vancouver, BC Canada, August 1–6, paper 9Google Scholar
  33. Liu GY, Wang YJ, Liu CW (2006) The seismic scenario simulation of electric power systems. In: First European conference on earthquake engineering and seismology, Geneva, Switzerland, 3–8 September, paper 200Google Scholar
  34. McGuire RK (2004) Seismic hazard and risk analysis. Earthquake Engineering Research Institute, Oakland, 240 pGoogle Scholar
  35. McVerry GH, Rhoades DA, Smith WD (2004) Joint hazard of earthquake shaking at multiple locations. In: Proceedings of the 13th world conference on earthquake engineering, Vancouver, Canada, August 1–6, paper 646Google Scholar
  36. Oral B, Dömnez F (2010) The impact of natural disasters on power systems: anatomy of the Marmara Earthquake Blackout. Acta Polytech Hung 7(2):107–118Google Scholar
  37. Park J, Bazzurro P, Baker JW (2007) Modeling spatial correlation of ground motion intensity measures for regional seismic hazard and portfolio loss estimations. In: Kanda J, Takada T, Furuta H (eds) Applications of statistics and probability in civil engineering. Taylor & Francis Group, London, pp 1–8Google Scholar
  38. Pitilakis K, Alexoudi M, Argyroudis S, Monge O, Martin C (2006) Vulnerability and risk assessment of lifelines. In: Oliveira CS, Roca A, Goula X (eds) Assessing and managing earthquake risk. Springer, Dordrecht, pp 185–212Google Scholar
  39. Poljanšek K, Bono F, Gutiérrez E (2012) Seismic risk assessment of interdependent critical infrastructure system: a case of European gas and electricity networks. Earthq Eng Struct Dyn 41:61–79. doi:10.1002/eqe.1118 CrossRefGoogle Scholar
  40. Portante EC, Kavicky JA, Folga SF, Craig BA, Talaber LE, Wulfkuhle GR (2010) Simulating the seismic performance of a large scale electric network in the U.S. midwest. In: Proceedings of the 2010 winter simulation conferenceGoogle Scholar
  41. Reed DA (2009a) Interdependence between power delivery and other lifelines. In: Tang AKK, Werner S (eds) Proceedings of the 2009 technical council on lifeline earthquake engineering (TCLEE) conference: lifeline earthquake engineering in a multihazard environment, Oakland, June 28–July 1. ASCE, Reston, VA, ISBN: 978-0-7844-1050-9, 1514 pp., doi:10.1061/41050(357)61
  42. Reed DA (2009b) Multi-hazard analysis of electric power delivery systems. In: Tang AKK, Werner S (eds) Proceedings of the 2009 technical council on lifeline earthquake engineering (TCLEE) conference: lifeline earthquake engineering in a multihazard environment, Oakland, June 28–July 1. ASCE, Reston, VA, ISBN: 978-0-7844-1050-9, 1514 pp. doi:10.1061/41050(357)30
  43. RMS event report (2000) Chi–Chi, Taiwan earthquake event report, risk management solutions. http://www.rms.com/publications/Taiwan_Event.pdf. (Last accessed 28 Mar 2013)
  44. Rhoades DA, McVerry GH (2001) Joint hazard of earthquake shaking at two or more locations. Earthq Spectra 17(4):697–710. doi:10.1193/1.1423903 CrossRefGoogle Scholar
  45. Selva J, Kakderi K, Alexoudi M, Pilitakis K (2011) Seismic performance of a system of interdependent lifeline and infrastructure components. In: Proceedings of the 8th international conference on urban earthquake engineering, March 7–8, Tokyo, JapanGoogle Scholar
  46. Shinozuka M, Dong X, Chen TC, Jin X (2007) Seismic performance of electric transmission network under component failures. Earthq Eng Struct Dyn 36:227–244CrossRefGoogle Scholar
  47. Sokolov V, Wenzel F (2008) First step toward realistic ground–motion prediction for SW-Germany. In: Proceedings of the workshop in “Seismicity patterns in the Euro-Mediterranean region”, European Center for Geodynamics and Seismology, November 17–19, Luxemburg, pp 53–68Google Scholar
  48. Sokolov V, Wenzel F (2011a) Influence of spatial correlation of strong ground–motion on uncertainty in earthquake loss estimation. Earthq Eng Struct Dyn 40:993–1009. doi:10.1002/eqe.1074 CrossRefGoogle Scholar
  49. Sokolov V, Wenzel F (2011b) Influence of ground–motion correlation on probabilistic assessments of seismic hazard and loss: sensitivity analysis. Bull Earthq Eng 9:1339–1360. doi:10.1007/s10518-011-9264-4 CrossRefGoogle Scholar
  50. Sokolov V, Wenzel F (2013a) Spatial correlation of ground–motions in estimating seismic hazard to civil infrastructure. In: Tesfamariam S, Goda K (eds) Seismic risk analysis and management of civil infrastructure systems. Woodhead, Cambridge, pp 57–78. doi:10.1533/9780857098986.1.57 Google Scholar
  51. Sokolov V, Wenzel F (2013b) Further analysis of the influence of site conditions and earthquake magnitude on ground–motion within–earthquake correlation: analysis of PGA and PGV data from the K-NET and the KiK-net (Japan) networks. Bull Earthq Eng 11(6):1909–1926. doi:10.1007/s10518-013-9493-9 CrossRefGoogle Scholar
  52. Sokolov V, Wenzel F, Jean WY, Wen KL (2010) Uncertainty and spatial correlation of earthquake ground motion in Taiwan. Terr Atmos Ocean Sci (TAO) 21:905–921. doi:10.3319/TAO.2010.05.03.01 CrossRefGoogle Scholar
  53. Sokolov V, Wenzel F, Wen KL, Jean WY (2012) On the influence of site conditions and earthquake magnitude on ground–motion within–earthquake correlation: analysis of PGA data from TSMIP (Taiwan) network. Bull Earthq Eng 10(5):1401–1429. doi:10.1007/s10518-012-9368-5 CrossRefGoogle Scholar
  54. Song J, Ok SY (2010) Multi-scale system reliability analysis of lifeline networks under earthquake hazards. Earthq Eng Struct Dyn 39(3):259–279. doi:10.1002/eqe.938 Google Scholar
  55. Wang M, Takada T (2005) Macrospatial correlation model of seismic ground motions. Earthq Spectra 21(4):1137–1156. doi:10.1193/1.2083887 CrossRefGoogle Scholar
  56. Wesson RL, Perkins DM (2001) Spatial correlation of probabilistic earthquake ground motion and loss. Bull Seismol Soc Am 91:1498–1515. doi:10.1785/0120000284 CrossRefGoogle Scholar
  57. Yang S, Zhao J (2009) An overview of earthquake mitigation of urban power system. In: The international conference on electrical engineering (ICEE 2009), Shenyang, China, paper I9FP0410. http://www.icee-con.org/papers/2009/pdf/2.05_I9FP0410_E.pdf. (Last accessed 28 Mar 2013)
  58. Yao B, Xie L, Huo E (2004) Study effect of lifeline interaction under seismic conditions. In: 13 world conference on earthquake engineering, Vancouver, BC, Canada, August 1–6, paper 3152Google Scholar
  59. Zhang X, Li Y, Li X, Liu Y, Lu T (2007) GIS-based earthquake hazard assessment of urban power systems: Memphis electric substations. In: Proceedings of the SPIE, vol 6754, geoinformatics 2007: geospatial information technology and applications, p 675403. doi:10.1117/12.764568

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Geophysical InstituteKarlsruhe Institute of Technology (KIT)KarlsruheGermany

Personalised recommendations