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Modeling Cascading Failures in Power Systems: Quasi-Steady-State Models and Dynamic Models

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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

The majority of efforts to model cascading failures in power systems leverage some type of computer simulation where one encodes the protective mechanisms of interest for the analysis at hand. The two main groups of simulators that researchers and practitioners use are: (i) quasi-steady-state (QSS) models, where most of the information for where the simulation goes next is captured in the current state of the system, and (ii) dynamic models, where one explicitly includes variables (and their necessary mathematical relationships) that keep a memory of the system elements (for example, generators or loads). In this chapter, we explore side to side the statistics and particular cascading path characteristics for two simulators that belong to the same family of codes, that is, they are both open source in the same programming language, tunable, and share a great part of the basic code infrastructure. One simulator is QSS and the second one is dynamic, that way we are able to explore differences that should stem from this characteristic, and not from major implementation discrepancies, as it has been observed in previous benchmarking efforts by relevant groups. We follow the analysis recommendations from the IEEE cascading failure working group in recent publications and present here new results for these two benchmarks.

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References

  1. F. Alanazi, J. Kim, E. Cotilla-Sanchez, Load oscillating attacks of smart grids: vulnerability analysis. IEEE Access 11, 36538–36549 (2023). ISSN: 2169-3536. https://doi.org/10.1109/ACCESS.2023.3266249. https://ieeexplore.ieee.org/document/10098782/ (visited on 08/29/2023)

  2. J. Bialek et al., Benchmarking and validation of cascading failure analysis tools. IEEE Trans. Power Syst. 31(6), 4887–4900 (2016). ISSN: 08858950. https://doi.org/10.1109/TPWRS.2016.2518660

    Article  Google Scholar 

  3. E. Cotilla-Sanchez, Big data and energy systems: efficient computational methods for the dynamic analysis of electric power infrastructure. PhD thesis. University of Vermont, 2012

    Google Scholar 

  4. E. Cotilla-Sanchez, ecotillasanchez/cosmic, Aug. 2023. https://github.com/ecotillasanchez/cosmic (visited on 08/30/2023)

  5. Y. Dai et al., Risk assessment and mitigation of cascading failures using critical line sensitivities. IEEE Trans. Power Syst., 1–12 (2023). ISSN: 0885-8950, 1558-0679. https://doi.org/10.1109/TPWRS.2023.3305093. https://ieeexplore.ieee.org/document/10219000/ (visited on 08/27/2023)

  6. M.J. Eppstein, P.D.H. Hines, A “random chemistry” algorithm for identifying collections of multiple contingencies that initiate cascading failure. IEEE Trans. Power Syst. 27(3), 1698–1705 (2012). ISBN: 9781479913039. ISSN: 08858950. https://doi.org/10.1109/TPWRS.2012.2183624

    Article  Google Scholar 

  7. R. Fitzmaurice, E. Cotilla-Sanchez, P. Hines, Evaluating the impact of modeling assumptions for cascading failure simulation, in IEEE Power and Energy Society General Meeting. ISSN: 19449925.2012. ISBN: 978-1-4673-2727-5. https://doi.org/10.1109/PESGM.2012.6345378

  8. A.J. Flueck et al., Dynamics and protection in cascading outages, in 2020 IEEE Power & Energy Society General Meeting (PESGM) (IEEE, Montreal, QC, Canada, Aug. 2020), pp. 1–5 ISBN: 978-1-72815-508-1. https://doi.org/10.1109/PESGM41954.2020.9281823. https://ieeexplore.ieee.org/document/9281823/ (visited on 08/30/2023)

  9. C. Grigg, P. Wong, The IEEE reliability test system—1996 a report prepared by the reliability test system task force of the application of probability methods subcommittee. IEEE Trans. Power Syst. 14(3), 1010–1020 (1999). ISBN: 0885-8950. ISSN: 08858950. https://doi.org/10.1109/59.780914

  10. P. Henneaux et al., A two-level probabilistic risk assessment of cascading outages. IEEE Trans. Power Syst. 31(3), 2393–2403 (2016)

    Article  Google Scholar 

  11. P. Henneaux et al., Benchmarking quasi-steady state cascading outage analysis methodologies, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) (IEEE, Boise, ID, June 2018), pp. 1–6. ISBN: 978-1-5386-3596-4. https://doi.org/10.1109/PMAPS.2018.8440212. https://ieeexplore.ieee.org/document/8440212/ (visited on 08/04/2023)

  12. P. Hines, DCSIMSEP, June 2023. https://github.com/phines/dcsimsep (visited on 08/30/2023)

  13. P. Hines, E. Cotilla-Sanchez, S. Blumsack, Do topological models provide good information about electricity infrastructure vulnerability? Chaos 20(3) (2010). arXiv:1002.2268. ISBN: 1054-1500. ISSN: 10541500. https://doi.org/10.1063/1.3489887

  14. W. Ju, K. Sun, R. Yao, Simulation of cascading outages using a power flow model considering frequency. IEEE Access (2018). IEEE, p. 1. https://doi.org/10.1109/ACCESS.2018.2851022

  15. C. Lassetter, E. Cotilla-Sanchez, J. Kim, A learning scheme for microgrid reconnection. IEEE Trans. Power Syst. 33(1), 691–700 (2018). ISSN: 0885-8950, 1558-0679. https://doi.org/10.1109/TPWRS.2017.2709741. http://ieeexplore.ieee.org/document/7935511/ (visited on 05/16/2020)

  16. L. Niu et al., A Hybrid Submodular Optimization Approach to Controlled Islanding with Post-Disturbance Stability Guarantees. arXiv:2302.10308 [cs, eess, math], Feb. 2023. http://arxiv.org/abs/2302.10308 (visited on 02/27/2023)

  17. 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). ISSN: 2076-3417. https://doi.org/10.3390/app10144761. https://www.mdpi.com/2076-3417/10/14/4761 (visited on 07/11/2020)

  18. M. Papic et al., Multiple outage challenges to transmission grid resilience, in 2019 IEEE Power & Energy Society General Meeting (PESGM) (IEEE, Atlanta, GA, USA, Aug. 2019), pp. 1–5. ISBN: 978-1-72811-981-6. https://doi.org/10.1109/PESGM40551.2019.8973606. https://ieeexplore.ieee.org/document/8973606/ (visited on 02/03/2020)

  19. P. Rezaei, P.D.H. Hines, M.J. Eppstein, Estimating cascading failure risk with random chemistry. IEEE Trans. Power Syst. 30(5), 2726–2735 (2015). arXiv:1405.4213. ISBN:9781467380409. ISSN: 08858950. https://doi.org/10.1109/TPWRS.2014.2361735

  20. L.F. Shampine, M.W. Reichelt, J.a. Kierzenka, Solving Index-1 DAEs in MATLAB and simulink. SIAM Rev. 41(3), 538–552 (1999). ISSN: 0036-1445. https://doi.org/10.1137/S003614459933425X

  21. J. Song et al., Dynamic modeling of cascading failure in power systems. IEEE Trans. Power Syst. 31(3), 2085–2095 (2016). arXiv:1411.3990. https://doi.org/10.1109/TPWRS.2015.2439237

  22. R. Yao et al., A multi-timescale quasi-dynamic model for simulation of cascading outages. IEEE Trans. Power Syst. 31(4), 3189–3201 (2016). ISSN: 08858950. https://doi.org/10.1109/TPWRS.2015.2466116

    Article  Google Scholar 

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Authors and Affiliations

  1. Kelley Engineering Center, Oregon State University, Corvallis, OR, USA

    Eduardo Cotilla-Sanchez

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  1. Eduardo Cotilla-Sanchez
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Correspondence to Eduardo Cotilla-Sanchez .

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Editors and Affiliations

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

    Kai Sun

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Cotilla-Sanchez, E. (2024). Modeling Cascading Failures in Power Systems: Quasi-Steady-State Models and Dynamic Models. 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_5

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  • DOI: https://doi.org/10.1007/978-3-031-48000-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47999-1

  • Online ISBN: 978-3-031-48000-3

  • eBook Packages: EnergyEnergy (R0)

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