TY - GEN
T1 - A Submodular Optimization Approach to Stable and Minimally Disruptive Controlled Islanding in Power Systems
AU - Sahabandu, Dinuka
AU - Niu, Luyao
AU - Clark, Andrew
AU - Poovendran, Radha
N1 - Publisher Copyright:
© 2022 American Automatic Control Council.
PY - 2022
Y1 - 2022
N2 - Power systems must maintain dynamical stability while meeting user demand in the presence of major disturbances including failures of multiple generators and transmission lines. One approach to mitigating disturbances is controlled islanding, in which a subset of edges is deliberately removed in order to partition the network into disjoint, internally stable and self-sufficient islands. In this paper, we present a submodular optimization approach to controlled islanding. We prove that computing optimal islands under three standard metrics, namely, generator coherence, load-generation imbalance, and power flow disruption, is equivalent to minimizing a supermodular function with a matroid basis constraint. Based on this result, we present the first polynomial-time islanding algorithms with constant-factor optimality bounds with respect to the three aforementioned metrics. We test the proposed approach on IEEE 30-bus, 57-bus, and 118-bus power systems. We demonstrate that our proposed algorithm converges and present the islanding strategies when different combinations of the metrics are considered.
AB - Power systems must maintain dynamical stability while meeting user demand in the presence of major disturbances including failures of multiple generators and transmission lines. One approach to mitigating disturbances is controlled islanding, in which a subset of edges is deliberately removed in order to partition the network into disjoint, internally stable and self-sufficient islands. In this paper, we present a submodular optimization approach to controlled islanding. We prove that computing optimal islands under three standard metrics, namely, generator coherence, load-generation imbalance, and power flow disruption, is equivalent to minimizing a supermodular function with a matroid basis constraint. Based on this result, we present the first polynomial-time islanding algorithms with constant-factor optimality bounds with respect to the three aforementioned metrics. We test the proposed approach on IEEE 30-bus, 57-bus, and 118-bus power systems. We demonstrate that our proposed algorithm converges and present the islanding strategies when different combinations of the metrics are considered.
UR - https://www.scopus.com/pages/publications/85138496521
U2 - 10.23919/ACC53348.2022.9867317
DO - 10.23919/ACC53348.2022.9867317
M3 - Conference contribution
AN - SCOPUS:85138496521
T3 - Proceedings of the American Control Conference
SP - 4587
EP - 4594
BT - 2022 American Control Conference, ACC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 American Control Conference, ACC 2022
Y2 - 8 June 2022 through 10 June 2022
ER -