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Analyzing Cascading Failures and Blackouts Using Utility Outage Data

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Cascading Failures in Power Grids

Part of the book series: Power Electronics and Power Systems ((PEPS))

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Abstract

Historical utility data for cascading failure and large blackouts is foundational for understanding and quantifying blackouts. This chapter surveys some of the main ideas in obtaining and exploiting the patterns in this data, beyond the useful lessons that can be learned from each particular blackout. Historical data on blackout size shows a heavy tailed distribution that implies that large blackouts are both rare and will occasionally occur, and that their risk is substantial. Detailed outage data is routinely collected by utilities and can be processed into cascading events or weather-related events. Metrics for these events can then be readily obtained. Almost all of the research on cascading is based on models and simulation, despite the promising and emerging opportunities to also learn from utility outage data. Some of these opportunities are outlined to encourage further work on real data: As well as its obvious key use to ground models and simulations in reality, the historical outage data can enable better contingency lists, be transformed into influence or interaction graphs, replace simulation by sampling, and describe typical blackouts and their restoration with Poisson processes.

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References

  1. D. Kosterev, C. Taylor, W. Mittelstadt, Model validation for the August 10, 1996 WSCC system outage. IEEE Trans. Power Syst. 14, 967–979 (1999)

    Article  Google Scholar 

  2. V. Venkatasubramanian, Y. Li, Analysis of 1996 Western American electric blackouts, in Bulk Power System Dynamics and Control - VI, Cortina d’Ampezzo, Italy, Aug 2004

    Google Scholar 

  3. US-Canada Power System Outage Task Force, Final Report on the August 14, 2003 Blackout in the United States and Canada (2004)

    Google Scholar 

  4. Federal Energy Regulatory Commission and the North American Electric Reliability Corporation, Arizona-Southern California Outages on September 8, 2011: Causes and Recommendations (2012)

    Google Scholar 

  5. IEEE PES PSDP Task Force on Blackout experience, mitigation, and role of new technologies, blackout experiences and lessons, Best practices for system dynamic performance, and the role of new technologies, IEEE Special Publication 07TP190, July 2007

    Google Scholar 

  6. I. Dobson, B.A. Carreras, V.E. Lynch, D.E. Newman, Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization. Chaos 17(2), 026103 (2007)

    Google Scholar 

  7. P. Hines, J. Apt, S. Talukdar, Large blackouts in North America: historical trends and policy implications. Energy Policy 37(12), 5249–5259 (2009)

    Article  Google Scholar 

  8. B.A. Carreras, D.E. Newman, I. Dobson, North American blackout time series statistics and implications for blackout risk. IEEE Trans. Power Syst. 31(6), 4406–4414 (2016)

    Article  Google Scholar 

  9. I. Dobson, S. Ekisheva, How long is a resilience event in a transmission system? Metrics and models driven by utility data. IEEE Trans. Power Syst. https://doi.org/10.1109/TPWRS.2023.3292328

  10. H. Ren, I. Dobson, B.A. Carreras, Long-term effect of the n-1 criterion on cascading line outages in an evolving power transmission grid. IEEE Trans. Power Syst. 23(3), 1217–1225 (2008)

    Article  Google Scholar 

  11. B.A. Carreras, D.E. Newman, I. Dobson, A.B. Poole, Evidence for self-organized criticality in a time series of electric power system blackouts. IEEE Trans. Circuits Syst. Part 1 51(9), 1733–1740 (2004)

    Google Scholar 

  12. D.E. Newman, B.A. Carreras, V.E. Lynch, I. Dobson, Exploring complex systems aspects of blackout risk and mitigation. IEEE Trans. Reliab. 60(1), 134–143 (2011)

    Article  Google Scholar 

  13. S. Ekisheva, R. Rieder, J. Norris, M. Lauby, I. Dobson, Impact of extreme weather on North American transmission system outages, in IEEE PES General Meeting, Washington DC USA, July 2021

    Google Scholar 

  14. S. Murphy, J. Apt, J. Moura, F. Sowell, Resource adequacy risks to the bulk power system in North America. Appl. Energy 212, 1360–1376 (2018). (Also see supplementary information)

    Google Scholar 

  15. S. Murphy, F. Sowell, J. Apt, A time-dependent model of generator failures and recoveries captures correlated events and quantifies temperature dependence. Appl. Energy 253, 113513 (2019). (Also see supplementary information).

    Google Scholar 

  16. NERC webpage www.nerc.com/pa/RAPA/tads

  17. Bonneville Power Administration transmission services operations & reliability, [Online]. Available: https://transmission.bpa.gov/Business/Operations/Outages/

  18. N.K. Carrington, I. Dobson, Z. Wang, Transmission grid outage statistics extracted from a web page logging outages in Northeast America, North American Power Symposium, College Station TX USA, November 2021

    Google Scholar 

  19. I. Dobson, Estimating the propagation and extent of cascading line outages from utility data with a branching process. IEEE Trans. Power Syst. 27(4), 2146–2155 (2012)

    Article  Google Scholar 

  20. R. Billinton, G. Singh, Application of adverse and extreme adverse weather: modeling in transmission and distribution system reliability evaluation. IEE Proc.-Gener. Transm. Distrib. 153(1), 115–120 (2006)

    Article  Google Scholar 

  21. R. Billinton, G. Singh, J. Acharya, Failure bunching phenomena in electric power transmission systems. Proc. Inst. Mech. Eng. Part O J. Risk Reliab. 220(1), (2006). https://doi.org/10.1243/1748006XJR

  22. N.K. Carrington, S. Ma, I. Dobson, Z. Wang, Extracting resilience statistics from utility data in distribution grids, in IEEE PES General Meeting, Montreal, Canada, Aug. 2020

    Google Scholar 

  23. M. Papic, S. Ekisheva, E. Cotilla-Sanchez, A risk-based approach to assess the operational resilience of transmission grids. Appl. Sci. 10(14), 4761 (2020)

    Google Scholar 

  24. M. Panteli, D.N. Trakas, P. Mancarella, n.d. Hatziargyriou, Power systems resilience assessment: hardening and smart operational enhancement. Proc. IEEE 105(7), 1202–1213 (2017)

    Google Scholar 

  25. A. Stankovic et al., Methods for analysis and quantification of power system resilience. IEEE Trans. Power Systems. 38(5), 4774–4787 (2023). https://doi.org/10.1109/TPWRS.2022.3212688

    Article  Google Scholar 

  26. E.A. Morris, K.R. Bell, I.M. Elders, Spatial and temporal clustering of fault events on the GB transmission network, in Probabilistic Methods Applied to Power Systems Conference, Beijing China, October 2016

    Google Scholar 

  27. S. Ekisheva, I. Dobson, J. Norris, R. Rieder, Assessing transmission resilience during extreme weather with outage and restore processes, in Probabilistic Methods Applied to Power Systems Conference, Manchester UK, June 2022

    Google Scholar 

  28. I. Dobson, Finding a Zipf distribution and cascading propagation metric in utility line outage data. Preprint (2018). arXiv:1808.08434 [physics.soc-ph]

    Google Scholar 

  29. IEEE Working Group on understanding, prediction, mitigation and restoration of cascading failures, Benchmarking and validation of cascading failure analysis tools. IEEE Trans. Power Syst. 31(6), 4887–4900 (2016)

    Google Scholar 

  30. P. Henneaux, E. Ciapessoni, D. Cirio, E. Cotilla-Sanchez, R. Diao, I. Dobson, A. Gaikwad, S. Miller, M. Papic, A. Pitto, J. Qi, N. Samaan, G. Sansavini, S. Uppalapati, R. Yao, Benchmarking quasi-steady state cascading outage analysis methodologies, in Probability Methods Applied to Power Systems, Boise, Idaho, USA June 2018

    Google Scholar 

  31. B.A. Carreras, D.E. Newman, I. Dobson, N.S. Degala, Validating OPA with WECC data, in Proc. 46th Hawaii Int. Conf. Syst. Sci. (HICSS), Maui, HI, USA, Jan. 2013, pp. 2197–2204

    Google Scholar 

  32. J. Qi, I. Dobson, S. Mei, Towards estimating the statistics of simulated cascades of outages with branching processes. IEEE Trans. Power Syst. 28(3), 3410–3419 (2013)

    Article  Google Scholar 

  33. P.D.H. Hines, I. Dobson, P. Rezaei, Cascading power outages propagate locally in an influence graph that is not the actual grid topology. IEEE Trans. Power Syst. 32(2), 958–967 (2017)

    Google Scholar 

  34. K. Zhou, I. Dobson, Z. Wang, The most frequent N-k line outages occur in motifs that can improve contingency selection. IEEE Trans. Power Syst. (2023). https://doi.org/10.1109/TPWRS.2023.3249825

  35. R. Milo et al., Network motifs: simple building blocks of complex networks. Science 298(5594), 824–827 (2002)

    Article  Google Scholar 

  36. Q. Chen, H. Ren, C. Sun, Z. Mi, D. Watts, Network motif as an indicator for cascading outages due to the decrease of connectivity, in IEEE PES General Meeting, Chicago, Illinois, USA, Jul. 2017

    Google Scholar 

  37. A.K. Dey, Y.R. Gel, H.V. Poor, What network motifs tell us about resilience and reliability of complex networks. Proc. Natl. Acad. Sci. 116(39), 19368–19373 (2019)

    Article  Google Scholar 

  38. A. Tajer, S.M. Perlaza, H.V. Poor, Advanced Data Analytics for Power Systems (Cambridge University Press, Cambridge, 2021)

    Book  Google Scholar 

  39. I. Dobson, B.A. Carreras, D.E. Newman, J.M. Reynolds-Barredo, Obtaining statistics of cascading line outages spreading in an electric transmission network from standard utility data. IEEE Trans. Power Syst. 31(6), 4831–4841 (2016)

    Article  Google Scholar 

  40. P.D.H. Hines, I. Dobson, E. Cotilla-Sanchez, M. Eppstein, “Dual graph” and “random chemistry” methods for cascading failure analysis, in Proc. 46th Hawaii Intl. Conf. Syst. Sci., Maui, HI, USA, Jan. 2013, pp. 2141–2150

    Google Scholar 

  41. J. Qi, K. Sun, S. Mei, An interaction model for simulation and mitigation of cascading failures. IEEE Trans. Power Syst. 30(2), 804–819 (2015)

    Article  Google Scholar 

  42. U. Nakarmi, M. Rahnamay-Naeini, M.J. Hossain, M.A. Hasnat, Interaction graphs for reliability analysis of power grids: A survey. Energies 13(9), 2219 (2020). https://doi.org/10.3390/en13092219

  43. K. Zhou, I. Dobson, Z. Wang, A. Roitershtein, A.P. Ghosh A Markovian influence graph formed from utility line outage data to mitigate large cascades. IEEE Trans. Power Syst. 35(4), 3224–3235 (2020)

    Article  Google Scholar 

  44. J. Qi, Utility outage data driven interaction networks for cascading failure analysis and mitigation. IEEE Trans. Power Syst. 36(2), 1409–1418 (2021)

    Article  Google Scholar 

  45. M.R. Kelly-Gorham, P.D.H. Hines, K. Zhou, I. Dobson, Using utility outage statistics to quantify improvements in bulk power system resilience, in Power Systems Computation Conference, Porto, Portugal, June 2020 and Electric Power Systems Research, vol 189, 106676, December 2020

    Google Scholar 

  46. M.R. Kelly-Gorham, P.D.H. Hines, I. Dobson, Ranking the impact of interdependencies on power system resilience using stratified sampling of utility data. IEEE Trans. Power Syst. https://doi.org/10.1109/TPWRS.2023.3260119

  47. B. Cheng, L. Nozick, I. Dobson, Investment planning for earthquake-resilient electric power systems considering cascading outages. Earthquake Spectra, 38(3), 1734–1760 (2022)

    Article  Google Scholar 

  48. S. Kancherla, I. Dobson, Heavy-tailed transmission line restoration times observed in utility data. IEEE Trans. Power Syst. 33(1), 1145–1147 (2018)

    Article  Google Scholar 

  49. F. Faghihi, P. Henneaux, P.E. Labeau, M. Panteli, An efficient probabilistic approach to dynamic resilience assessment of power systems, Congrès Lambda Mu 22 “Les risques au coeur des transitions, (e-congrès)-22e Congrès Maîtrise des Risques Sûreté Fonctionnement, 2020

    Google Scholar 

  50. C. Nan, G. Sansavini, A quantitative method for assessing resilience of interdependent infrastructures. Reliab. Eng. Syst. Safety 157, 35–53 (2017)

    Article  Google Scholar 

  51. S. Poudel, A. Dubey, A. Bose, Risk-based probabilistic quantification of power distribution system operational resilience. IEEE Syst. J. 14(3), 3506–3517 (2020)

    Article  Google Scholar 

  52. N.K. Carrington, I. Dobson, Z. Wang, Extracting resilience metrics from distribution utility data using outage and restore process statistics. IEEE Trans. Power Syst. 36(2), 5814–5823 (2021)

    Article  Google Scholar 

  53. NERC, 2022 State of reliability, An assessment of 2021 bulk power system performance, July 2022. Available: www.nerc.com

  54. M. Barkakati, A. Pal, A comprehensive data driven outage analysis for assessing reliability of the bulk power system, in IEEE PES General Meeting, Atlanta, GA, USA, 2019

    Google Scholar 

  55. C.J. Zapata, S.C. Silva, H.I. Gonzalez, O.L. Burbano, J.A. Hernandez, Modeling the repair process of a power distribution system, in IEEE/PES T&D Conf. & Exp.: Latin America, Bogota, Columbia, 2008

    Google Scholar 

  56. Y. Wei, C. Ji, F. Galvan, S. Couvillon, G. Orellana, J. Momoh, Non-stationary random process for large-scale failure and recovery of power distribution. Appl. Math. 7(3), 233–249 (2016)

    Article  Google Scholar 

  57. I. Dobson, Models, metrics, and their formulas for typical electric power system resilience events. IEEE Trans. Power Syst. https://doi.org/10.1109/TPWRS.2023.3300125

  58. M. Noebels, I. Dobson, M. Panteli, Observed acceleration of cascading outages. IEEE Trans. Power Syst. 36(4), 3821–3823 (2021)

    Article  Google Scholar 

  59. B.A. Carreras, J. M. Reynolds Barredo, I. Dobson, D.E. Newman, Validating the OPA cascading blackout model on a 19402 bus transmission network with both mesh and tree structures, in Fifty-Second Hawaii International Conference on System Sciences, Maui, HI, January 2019

    Google Scholar 

  60. M. Noebels, R Preece, M. Panteli, AC cascading failure model for resilience analysis in power networks. IEEE Syst. J. 16(1), 374–385 (2022)

    Google Scholar 

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Authors and Affiliations

  1. ECpE Department, Iowa State University, Ames, IA, USA

    Ian Dobson

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  1. Ian Dobson
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Correspondence to Ian Dobson .

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  1. Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Knoxville, TN, USA

    Kai Sun

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Dobson, I. (2024). Analyzing Cascading Failures and Blackouts Using Utility Outage Data. In: Sun, K. (eds) Cascading Failures in Power Grids. Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-48000-3_2

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  • DOI: https://doi.org/10.1007/978-3-031-48000-3_2

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