Electric Power Grid Restoration Considering Disaster Economics

dc.contributor.authorArab, Ali
dc.contributor.authorKhodaei, Amin
dc.contributor.authorKhator, Suresh K.
dc.contributor.authorHan, Zhu
dc.date.accessioned2020-05-11T16:14:50Z
dc.date.available2020-05-11T16:14:50Z
dc.date.issued2/1/2016
dc.description.abstractThis paper presents a cost-effective system-level restoration scheme to improve power grids resilience by efficient response to the damages due to natural or manmade disasters. A post-disaster decision making model is developed to find the optimal repair schedule, unit commitment solution, and system configuration in restoration of the damaged power grid. The physical constraints of the power grid, associated with the unit commitment and restoration, are considered in the proposed model. The value of lost load is used as a viable measure to represent the criticality of each load in the power grid. The model is formulated as a mixed-integer program and, then, is decomposed into an integer master problem and a dual linear subproblem to be solved using Benders decomposition algorithm. Different scenarios are developed to analyze the proposed model on the standard IEEE 118-bus test system. This paper provides a prototype and a proof of concept for utility companies to consider economics of disaster and include unit commitment model into the post-disaster restoration process.
dc.identifier.citationCopyright 2016 IEEE Access. Recommended citation: Arab, Ali, Amin Khodaei, Suresh K. Khator, and Zhu Han. "Electric power grid restoration considering disaster economics." IEEE Access 4 (2016): 639-649. DOI: 10.1109/ACCESS.2016.2523545. URL: https://ieeexplore.ieee.org/abstract/document/7395278. Reproduced in accordance with the original publisher's licensing terms and with permission from the author(s).
dc.identifier.urihttps://hdl.handle.net/10657/6450
dc.publisherIEEE Access
dc.subjectDisaster management
dc.subjectpower grid
dc.subjectrestoration
dc.subjectunit commitment
dc.titleElectric Power Grid Restoration Considering Disaster Economics
dc.typeArticle

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