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Resilient Scheduling of Control Software Updates in Power Distribution Systems
Natl Sun Yat Sen Univ, Dept Elect Engn, Kaohsiung, Taiwan..
KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Reglerteknik.ORCID-id: 0000-0003-1835-2963
2022 (Engelska)Ingår i: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2022, s. 6146-6153Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In response to newly found security vulnerabilities, or as part of a moving target defense, a fast and safe control software update scheme for networked control systems is highly desirable. We here develop such a scheme for intelligent electronic devices (IEDs) in power distribution systems, which is a solution to the so-called software update rollout problem. This problem seeks to minimize the makespan of the software rollout, while at the same time guaranteeing acceptable voltage and current levels at all buses despite possible worst-case update failure where malfunctioning IEDs may inject harmful amount of power into the system. Utilizing the nonlinear DistFlow equations, we can rewrite the voltage and current conditions as a set of load and network dependent linear inequalities with respect to the rollout schedule with quantifiable degree of conservatism. Assuming update failure detectors such as out-of-range voltage relays, the optimal software rollout schedule can be time-slotted so that the rollout problem can be reformulated as a variant of the classical combinatorial bin packing problem. Demonstration with a realistic distribution system benchmark is provided to verify the practical significance of our work.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE) , 2022. s. 6146-6153
Serie
IEEE Conference on Decision and Control, ISSN 0743-1546
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:kth:diva-326431DOI: 10.1109/CDC51059.2022.9993270ISI: 000948128105031Scopus ID: 2-s2.0-85147016156OAI: oai:DiVA.org:kth-326431DiVA, id: diva2:1754295
Konferens
IEEE 61st Conference on Decision and Control (CDC), DEC 06-09, 2022, Cancun, MEXICO
Anmärkning

QC 20230503

Tillgänglig från: 2023-05-03 Skapad: 2023-05-03 Senast uppdaterad: 2023-05-03Bibliografiskt granskad

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Sandberg, Henrik

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