Published December 2019 | Version Submitted
Book Section - Chapter Open

Less is More: Real-time Failure Localization in Power Systems

Abstract

Cascading failures in power systems exhibit nonlocal propagation patterns, which make the analysis and mitigation of failures difficult. In this work, we propose a distributed control framework inspired by the recently proposed concepts of unified controller and network tree-partition that offers strong guarantees in both the mitigation and localization of cascading failures in power systems. In this framework, the transmission network is partitioned into several control areas which are connected in a tree structure, and the unified controller is adopted by generators or controllable loads for fast timescale disturbance response. After an initial failure, the proposed strategy always prevents successive failures from happening, and regulates the system to the desired steady state where the impact of initial failures are localized as much as possible. For extreme failures that cannot be localized, the proposed framework has a configurable design, that progressively involves and coordinates more control areas for failure mitigation and, as a last resort, imposes minimal load shedding. We compare the proposed control framework with Automatic Generation Control (AGC) on the IEEE 118-bus test system. Simulation results show that our novel framework greatly improves the system robustness in terms of the N - 1 security standard, and localizes the impact of initial failures in majority of the load profiles that are examined. Moreover, the proposed framework incurs significantly less load loss, if any, compared to AGC.

Additional Information

© 2019 IEEE. This work has been supported by Resnick Fellowship, Linde Institute Research Award, NWO Rubicon grant 680.50.1529., 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.

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Additional details

Identifiers

Eprint ID
96748
DOI
10.1109/CDC40024.2019.9029393
Resolver ID
CaltechAUTHORS:20190626-143544929

Funding

Resnick Sustainability Institute
Linde Institute of Economic and Management Science
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)
680.50.1529
NSF
IIP-1602119
NSF
ECCS-1619352
NSF
CNS-1545096
NSF
CCF-1637598
NSF
ECCS-1619352
NSF
CNS-1518941
NSF
CPS-154471
NSF
CCF-1637598
Advanced Research Projects Agency-Energy (ARPA-E)
DE-AR0000699
Defense Threat Reduction Agency (DTRA)
HDTRA 1-15-1-0003
Skoltech
1075-MRA

Dates

Created
2019-06-27
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field

Caltech Custom Metadata

Caltech groups
Resnick Sustainability Institute