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Resilient Distribution Network Planning Against Dynamic Malicious Power Injection Attacks
The University of Tokyo, Department of Information Physics and Computing, Graduate School of Information Science and Technology, Tokyo, Japan.ORCID iD: 0000-0002-8598-0348
Institute of Science Tokyo, Department of Systems and Control Engineering, School of Engineering, Tokyo, Japan.
Institute of Science Tokyo, Department of Systems and Control Engineering, School of Engineering, Tokyo, Japan.ORCID iD: 0000-0002-9273-134X
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1835-2963
2026 (English)In: IEEE Transactions on Control of Network Systems, E-ISSN 2325-5870, Vol. 13, no 1, p. 449-461Article in journal (Refereed) Published
Abstract [en]

Active distribution networks facilitating bidirectional power exchange with renewable energy resources are susceptible to cyberattacks due to integration of a diverse array of cyber components. This study introduces a grid-level defense strategy aimed at enhancing attack resiliency based on distribution network planning. Our proposed framework imposes a security requirement into existing planning methodologies, ensuring that voltage deviation from its rated value remains within a tolerable range against dynamically and maliciously injected power at end-user nodes. Unfortunately, the formulated problem in its original form is intractable because it is an infinite-dimensional bi-level optimization problem over a function space. To address this complexity, we develop an equivalent transformation into a tractable form as mixed- integer linear program leveraging linear dynamical system theory and graph theory. Notably, our investigation reveals that the severity of potential attacks hinges solely on the cumulative reactances over the path from the substation to the targeted node, thereby reducing the problem to a finite-dimensional problem. Further, the bi-level optimization problem is reduced to a single-level optimization problem by using a technique utilized in solving the shortest path problem. Through extensive numerical simulations conducted on a 54-node distribution network benchmark, our proposed methodology exhibits a noteworthy 29.3% enhancement in the resiliency, with a mere 2.1% uptick in the economic cost.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2026. Vol. 13, no 1, p. 449-461
Keywords [en]
Distribution network planning, power injection attack, resilient distribution systems
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-375318DOI: 10.1109/TCNS.2025.3648474ISI: 001719577900003Scopus ID: 2-s2.0-105026087363OAI: oai:DiVA.org:kth-375318DiVA, id: diva2:2028598
Note

QC 20260320

Available from: 2026-01-15 Created: 2026-01-15 Last updated: 2026-05-29Bibliographically approved

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Sandberg, Henrik

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