Probabilistic N-k failure-identification for power systems

Sundar, Kaarthik; Coffrin, Carleton; Nagarajan, Harsha; Bent, Russell

doi:10.1002/net.21806

Title: Probabilistic N-k failure-identification for power systems

Journal Article · Mon Jan 22 00:00:00 EST 2018 · Networks

DOI:https://doi.org/10.1002/net.21806· OSTI ID:1463479

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Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

This work considers a probabilistic generalization of the N-k failure-identification problem in power transmission networks, where the probability of failure of each component in the network is known a priori and the goal of the problem is to find a set of k components that maximizes disruption to the system loads weighted by the probability of simultaneous failure of the k components. The resulting problem is formulated as a bilevel mixed-integer nonlinear program. Convex relaxations, linear approximations, and heuristics are developed to obtain feasible solutions that are close to the optimum. A general cutting-plane algorithm is proposed to solve the convex relaxation and linear approximations of the N-k problem. Extensive numerical results corroborate the effectiveness of the proposed algorithms on small-, medium-, and large-scale test instances; the test instances include the IEEE 14-bus system, the IEEE single-area and three-area RTS96 systems, the IEEE 118-bus system, the WECC 240-bus test system, the 1354-bus PEGASE system, and the 2383-bus Polish winter-peak test system.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1463479

Report Number(s):: LA-UR-17-23601

Journal Information:: Networks, Vol. 71, Issue 3; ISSN 0028-3045

Country of Publication:: United States

Language:: English

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Cited by: 15 works

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Title: Probabilistic N-k failure-identification for power systems

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