The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

Hussain, Tanveer; Alam, S. M. Shafiul; Hansen, Timothy M.; Suryanarayanan, Siddharth

doi:10.1049/tje2.12081

The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

Journal Article · Tue Oct 05 00:00:00 EDT 2021 · Journal of Engineering

DOI:https://doi.org/10.1049/tje2.12081· OSTI ID:1824707

^[1]; ^[2]; ^[1]; Suryanarayanan, Siddharth ^[1]

Electrical Engineering and Computer Science Department South Dakota State University Brookings South Dakota USA
Power and Energy Systems Idaho National Laboratory Idaho Falls Idaho USA

Abstract

A computationally improved algorithm is presented to find the best transmission switching (TS) candidate for boosting resilience of electricity grids subject to ( N ‐2) contingencies. Here, resilience is computed as the reduction in load shed after the above‐mentioned ( N‐ ) contingencies. TS is a planned line outage, and past research shows that changing the transmission system's topology changes the power flow and removes post contingency violations. Finding the best TS candidate in a computationally suitable time for effectively boosting resilience is a challenge. The best TS candidate is found using a novel heuristic method by decreasing the search space based on proximity to the bus with the maximum load shedding (LSB). The LSB algorithm is faster than existing algorithms in the literature; and, it is compatible with both the AC and DC optimal power flow formulations. To validate the authors' claims of speedup and accuracy, two metrics are used to analyze the results from the IEEE 39‐bus and 118‐bus systems. Finally, the inherent parallelism of the LSB algorithm is leveraged on a high‐performance computing platform and applied to the large‐scale Polish 2383‐bus test system to validate scalability in both size and speedup in computation time.

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Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC07-05ID14517

Other Award/Contract Number:: INL Laboratory Directed Research & Development (LDR)
Roaring Thunder cluster at SDSU funded under NSF
CNS‐1726946

OSTI ID:: 1824707

Alternate ID(s):: OSTI ID: 1824708
OSTI ID: 1845959

Report Number(s):: INL/JOU-21-61530-Rev001

Journal Information:: Journal of Engineering, Journal Name: Journal of Engineering Journal Issue: 12 Vol. 2021; ISSN 2051-3305

Publisher:: Institution of Engineering and Technology (IET)Copyright Statement

Country of Publication:: United States

Language:: English

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