IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v102y2012icp41-52.html
   My bibliography  Save this article

A level-1 probabilistic risk assessment to blackout hazard in transmission power systems

Author

Listed:
  • Henneaux, Pierre
  • Labeau, Pierre-Etienne
  • Maun, Jean-Claude

Abstract

The blackout risk in power systems is difficult to estimate by actual probabilistic methods because they usually neglect, or do not properly consider, the dependencies between failures and the dynamic evolution of the grid in the course of a transient. Our purpose is therefore to develop an integrated probabilistic approach to blackout analysis, capable of handling the coupling between events in cascading failure, and the dynamic response of the grid to stochastic initiating perturbations. This approach is adapted from dynamic reliability methodologies. This paper focuses on the modeling adopted for the first phase of a blackout, ruled by thermal transients. The goal is to identify dangerous cascading scenarios and better calculate their frequency. A Monte Carlo code specifically developed for this purpose is validated on a test grid. Some dangerous scenarios are presented and their frequency calculated by this method is compared with a more classical estimation neglecting thermal effects, showing significant differences. In particular, our method can reveal dangerous scenarios neglected or underestimated by the more classical method because they do not take into account the increase of failure rates in stress conditions.

Suggested Citation

  • Henneaux, Pierre & Labeau, Pierre-Etienne & Maun, Jean-Claude, 2012. "A level-1 probabilistic risk assessment to blackout hazard in transmission power systems," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 41-52.
    • Handle: RePEc:eee:reensy:v:102:y:2012:i:c:p:41-52
    DOI: 10.1016/j.ress.2012.02.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832012000221
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2012.02.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Haarla, Liisa & Pulkkinen, Urho & Koskinen, Mikko & Jyrinsalo, Jussi, 2008. "A method for analysing the reliability of a transmission grid," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 277-287.
    2. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    2. Muhammad Murtadha Othman & Nur Ashida Salim & Ismail Musirin, 2017. "Sustainability from the Occurrence of Critical Dynamic Power System Blackout Determined by Using the Stochastic Event Tree Technique," Sustainability, MDPI, vol. 9(6), pages 1-17, June.
    3. Kosai, Shoki & Unesaki, Hironobu, 2017. "Quantitative analysis on the impact of nuclear energy supply disruption on electricity supply security," Applied Energy, Elsevier, vol. 208(C), pages 1198-1207.
    4. Guo, Hengdao & Zheng, Ciyan & Iu, Herbert Ho-Ching & Fernando, Tyrone, 2017. "A critical review of cascading failure analysis and modeling of power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 9-22.
    5. Diao, Xiaoxu & Zhao, Yunfei & Smidts, Carol & Vaddi, Pavan Kumar & Li, Ruixuan & Lei, Hangtian & Chakhchoukh, Yacine & Johnson, Brian & Blanc, Katya Le, 2024. "Dynamic probabilistic risk assessment for electric grid cybersecurity," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    6. Agnieszka Bieda & Agnieszka Cienciała, 2021. "Towards a Renewable Energy Source Cadastre—A Review of Examples from around the World," Energies, MDPI, vol. 14(23), pages 1-34, December.
    7. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    8. Shoki Kosai & Chia Kwang Tan & Eiji Yamasue, 2018. "Evaluating Power Reliability Dedicated for Sudden Disruptions: Its Application to Determine Capacity on the Basis of Energy Security," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    9. Kamyab, Shahabeddin & Nematollahi, Mohammadreza & Henneaux, Pierre & Labeau, Pierre-Etienne, 2021. "Development of a hybrid method to assess grid-related LOOP scenarios for an NPP," Reliability Engineering and System Safety, Elsevier, vol. 206(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdul Rahman, Fariz & Varuttamaseni, Athi & Kintner-Meyer, Michael & Lee, John C., 2013. "Application of fault tree analysis for customer reliability assessment of a distribution power system," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 76-85.
    2. Kamyab, Shahabeddin & Nematollahi, Mohammadreza & Henneaux, Pierre & Labeau, Pierre-Etienne, 2021. "Development of a hybrid method to assess grid-related LOOP scenarios for an NPP," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    3. Vaurio, Jussi K., 2011. "Importance measures in risk-informed decision making: Ranking, optimisation and configuration control," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1426-1436.
    4. Leonardo Leoni & Farshad BahooToroody & Saeed Khalaj & Filippo De Carlo & Ahmad BahooToroody & Mohammad Mahdi Abaei, 2021. "Bayesian Estimation for Reliability Engineering: Addressing the Influence of Prior Choice," IJERPH, MDPI, vol. 18(7), pages 1-16, March.
    5. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "A new efficient algorithm for finding all d-minimal cuts in multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 151-163.
    6. Wu, Baichao & Tang, Aiping & Wu, Jie, 2016. "Modeling cascading failures in interdependent infrastructures under terrorist attacks," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 1-8.
    7. Cheng, Shikun & Li, Zifu & Mang, Heinz-Peter & Neupane, Kalidas & Wauthelet, Marc & Huba, Elisabeth-Maria, 2014. "Application of fault tree approach for technical assessment of small-sized biogas systems in Nepal," Applied Energy, Elsevier, vol. 113(C), pages 1372-1381.
    8. Darwish, Molham & Almouahed, Shaban & de Lamotte, Florent, 2017. "The integration of expert-defined importance factors to enrich Bayesian Fault Tree Analysis," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 81-90.
    9. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
    10. Zheng, Junjun & Okamura, Hiroyuki & Pang, Taoming & Dohi, Tadashi, 2021. "Availability importance measures of components in smart electric power grid systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    11. Hamzeh Soltanali & Mehdi Khojastehpour & José Torres Farinha & José Edmundo de Almeida e Pais, 2021. "An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing," Energies, MDPI, vol. 14(22), pages 1-21, November.
    12. Sharma, Neetesh & Gardoni, Paolo, 2022. "Mathematical modeling of interdependent infrastructure: An object-oriented approach for generalized network-system analysis," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    13. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    14. Lilian. O. Iheukwumere-Esotu & Akilu Yunusa Kaltungo, 2020. "Assessment of Barriers to Knowledge and Experience Transfer in Major Maintenance Activities," Energies, MDPI, vol. 13(7), pages 1-24, April.
    15. Kai Pan & Hui Liu & Xiaoqing Gou & Rui Huang & Dong Ye & Haining Wang & Adam Glowacz & Jie Kong, 2022. "Towards a Systematic Description of Fault Tree Analysis Studies Using Informetric Mapping," Sustainability, MDPI, vol. 14(18), pages 1-28, September.
    16. Taleb-Berrouane, Mohammed & Khan, Faisal & Amyotte, Paul, 2020. "Bayesian Stochastic Petri Nets (BSPN) - A new modelling tool for dynamic safety and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    17. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    18. Guopeng Song & Hao Chen & Bo Guo, 2014. "A Layered Fault Tree Model for Reliability Evaluation of Smart Grids," Energies, MDPI, vol. 7(8), pages 1-23, July.
    19. Salman, Abdullahi M. & Li, Yue & Bastidas-Arteaga, Emilio, 2017. "Maintenance optimization for power distribution systems subjected to hurricane hazard, timber decay and climate change," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 136-149.
    20. Sherwin, Michael D. & Medal, Hugh & Lapp, Steven A., 2016. "Proactive cost-effective identification and mitigation of supply delay risks in a low volume high value supply chain using fault-tree analysis," International Journal of Production Economics, Elsevier, vol. 175(C), pages 153-163.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:102:y:2012:i:c:p:41-52. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.