A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events
The extent of the damage to Puerto Rico from Hurricane Maria in September 2017 led to outages in electricity service that persisted for months. Power system operators attempting to restore critical facilities faced challenges on almost every front, from supply chain interruptions to the inaccessibil...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Open Access Journal of Power and Energy |
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| Online Access: | https://ieeexplore.ieee.org/document/9927237/ |
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| author | Emily L. Barrett Kaveri Mahapatra Marcelo Elizondo Xiaoyuan Fan Sarah Davis Sarah Newman Patrick Royer Bharat Vyakaranam Fernando Bereta Dos Reis Xinda Ke Jeff Dagle |
| author_facet | Emily L. Barrett Kaveri Mahapatra Marcelo Elizondo Xiaoyuan Fan Sarah Davis Sarah Newman Patrick Royer Bharat Vyakaranam Fernando Bereta Dos Reis Xinda Ke Jeff Dagle |
| author_sort | Emily L. Barrett |
| collection | DOAJ |
| description | The extent of the damage to Puerto Rico from Hurricane Maria in September 2017 led to outages in electricity service that persisted for months. Power system operators attempting to restore critical facilities faced challenges on almost every front, from supply chain interruptions to the inaccessibility of key assets. After a disaster of this magnitude, it is critical, but challenging, to prioritize how limited resources are directed toward rebuilding and fortifying the electric power system. To inform these decisions, the U.S. Department of Energy funded efforts investigating methodologies to identify critical vulnerabilities to the Puerto Rican power system, and to provide data-driven recommendations on how to harden and operate the system for greater resilience. This work presents the Risk-based Contingency Analysis Tool (RCAT), a framework developed as a part of that resilience initiative. The framework can qualitatively and quantitatively describe the most critical system vulnerabilities with an understanding of both likelihood of occurrence and impact. It evaluates the effectiveness of candidate remediation strategies in reducing overall risk to the system from future hurricane events. This paper will describe RCAT, with an emphasis on how different modeling capabilities have been integrated along with probabilistic methods and analytical metrics to better describe risk. |
| format | Article |
| id | doaj-art-fb64ea79740743d7b2185aaa8e12b7ad |
| institution | DOAJ |
| issn | 2687-7910 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Access Journal of Power and Energy |
| spelling | doaj-art-fb64ea79740743d7b2185aaa8e12b7ad2025-08-20T03:21:30ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102023-01-0110253510.1109/OAJPE.2022.32141759927237A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme EventsEmily L. Barrett0https://orcid.org/0000-0003-0072-0318Kaveri Mahapatra1Marcelo Elizondo2Xiaoyuan Fan3https://orcid.org/0000-0003-3868-8106Sarah Davis4Sarah Newman5Patrick Royer6https://orcid.org/0000-0001-9160-3963Bharat Vyakaranam7https://orcid.org/0000-0002-3379-9635Fernando Bereta Dos Reis8Xinda Ke9Jeff Dagle10https://orcid.org/0000-0002-0316-5455Department of Electricity Infrastructure, Pacific Northwest National Laboratory, Richland, WA, USADepartment of Electricity Security, Pacific Northwest National Laboratory, Richland, WA, USAPacific Northwest National Laboratory, Energy and Efficiency Division, Seattle, WA, USADepartment of Electricity Infrastructure, Pacific Northwest National Laboratory, Richland, WA, USAApex Clean Energy, Charlottesville, VA, USAPacific Northwest National Laboratory, Richland, WA, USAPacific Northwest National Laboratory, Richland, WA, USADepartment of Electricity Security, Pacific Northwest National Laboratory, Richland, WA, USAPacific Northwest National Laboratory, Richland, WA, USADepartment of Energy and Environment, Pacific Northwest National Laboratory, Richland, WA, USAPacific Northwest National Laboratory, Richland, WA, USAThe extent of the damage to Puerto Rico from Hurricane Maria in September 2017 led to outages in electricity service that persisted for months. Power system operators attempting to restore critical facilities faced challenges on almost every front, from supply chain interruptions to the inaccessibility of key assets. After a disaster of this magnitude, it is critical, but challenging, to prioritize how limited resources are directed toward rebuilding and fortifying the electric power system. To inform these decisions, the U.S. Department of Energy funded efforts investigating methodologies to identify critical vulnerabilities to the Puerto Rican power system, and to provide data-driven recommendations on how to harden and operate the system for greater resilience. This work presents the Risk-based Contingency Analysis Tool (RCAT), a framework developed as a part of that resilience initiative. The framework can qualitatively and quantitatively describe the most critical system vulnerabilities with an understanding of both likelihood of occurrence and impact. It evaluates the effectiveness of candidate remediation strategies in reducing overall risk to the system from future hurricane events. This paper will describe RCAT, with an emphasis on how different modeling capabilities have been integrated along with probabilistic methods and analytical metrics to better describe risk.https://ieeexplore.ieee.org/document/9927237/Bulk electric systemhurricane eventspower system planningpower system resilienceprobabilistic risk-based analysis |
| spellingShingle | Emily L. Barrett Kaveri Mahapatra Marcelo Elizondo Xiaoyuan Fan Sarah Davis Sarah Newman Patrick Royer Bharat Vyakaranam Fernando Bereta Dos Reis Xinda Ke Jeff Dagle A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events IEEE Open Access Journal of Power and Energy Bulk electric system hurricane events power system planning power system resilience probabilistic risk-based analysis |
| title | A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events |
| title_full | A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events |
| title_fullStr | A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events |
| title_full_unstemmed | A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events |
| title_short | A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events |
| title_sort | risk based framework for power system modeling to improve resilience to extreme events |
| topic | Bulk electric system hurricane events power system planning power system resilience probabilistic risk-based analysis |
| url | https://ieeexplore.ieee.org/document/9927237/ |
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