Du, M., Zhang, J. orcid.org/0000-0002-6188-4108, Gu, C. orcid.org/0000-0002-3306-767X et al. (1 more author) (2024) Resilience improving strategy for power systems with high wind power penetration against uncertain attacks. IEEE Transactions on Sustainable Energy, 15 (4). pp. 2625-2637. ISSN 1949-3029
Abstract
This paper aims to produce a practical and efficient decision for the system operator to harden critical components in power systems with high wind power penetration against uncertain attacks. Thus, an adjustable robust tri-level defender-attacker-defender (ART-DAD) model is proposed to improve the resilience of power systems by hardening critical transmission lines. The proposed ART-DAD model considers both uncertain attacks and uncertain wind power output, which provides meaningful insights into the resilience improvement of power systems that involve uncertainties. More specifically, the proposed defense model integrates dynamic N-K criterion for attack budgets and the polyhedral uncertainty set for wind power output to develop resilient line hardening strategies. The proposed defense model can be formulated as a mixed integer tri-level programming problem that is decoupled into a master and sub-problem. Then, a constraint-generation based solution algorithm is proposed to solve the overall ART-DAD model with a master and sub-problem scheme. Simulation results on IEEE RTS-79 and RTS-96 systems validate the effectiveness of the proposed resilience improving strategy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in IEEE Transactions on Sustainable Energy is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Wind power generation; Power systems; Uncertainty; Resilience; Wind turbines; Indexes; Random variables |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number UK Research and Innovation MR/W011360/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Jul 2024 13:18 |
Last Modified: | 20 Nov 2024 16:01 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/tste.2024.3430844 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215006 |