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A Spectral Representation of Power Systems with Applications to Adaptive Grid Partitioning and Cascading Failure Localization

Zocca, Alessandro and Liang, Chen and Guo, Linqi and Low, Steven H. and Wierman, Adam (2021) A Spectral Representation of Power Systems with Applications to Adaptive Grid Partitioning and Cascading Failure Localization. . (Unpublished)

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Transmission line failures in power systems propagate and cascade non-locally. This well-known yet counter-intuitive feature makes it even more challenging to optimally and reliably operate these complex networks. In this work we present a comprehensive framework based on spectral graph theory that fully and rigorously captures how multiple simultaneous line failures propagate, distinguishing between non-cut and cut set outages. Using this spectral representation of power systems, we identify the crucial graph sub-structure that ensures line failure localization -- the network bridge-block decomposition. Leveraging this theory, we propose an adaptive network topology reconfiguration paradigm that uses a two-stage algorithm where the first stage aims to identify optimal clusters using the notion of network modularity and the second stage refines the clusters by means of optimal line switching actions. Our proposed methodology is illustrated using extensive numerical examples on standard IEEE networks and we discussed several extensions and variants of the proposed algorithm.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Zocca, Alessandro0000-0001-6585-4785
Low, Steven H.0000-0001-6476-3048
Additional Information:Attribution 4.0 International (CC BY 4.0). This research has been supported by NWO Rubicon grant 680.50.1529, Resnick Fellowship, Linde Institute Research Award, NSF grants through PFI:AIR-TT award 1602119, EPCN 1619352, CNS 1545096, CCF 1637598, ECCS 1619352, CNS 1518941, CPS 154471, AitF 1637598, ARPA-E grant through award DE-AR0000699 (NODES) and GRID DATA, DTRA through grant HDTRA 1-15-1-0003 and Skoltech through collaboration agreement 1075-MRA.
Group:Resnick Sustainability Institute
Funding AgencyGrant Number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)680.50.1529
Linde Institute of Economic and Management ScienceUNSPECIFIED
Advanced Research Projects Agency-Energy (ARPA-E)DE-AR0000699
Defense Threat Reduction Agency (DTRA)HDTRA 1-15-1-0003
Resnick Sustainability InstituteUNSPECIFIED
Record Number:CaltechAUTHORS:20210716-225840003
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109904
Deposited By: George Porter
Deposited On:19 Jul 2021 17:48
Last Modified:19 Jul 2021 17:48

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