Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

Ma, Shuyang; Li, Yan; Du, Liang; Wu, Jianzhong; Zhou, Yue; Zhang, Yichen; Xu, Tao

doi:10.1016/j.apenergy.2021.118056

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

Journal Article · Tue Nov 02 00:00:00 EDT 2021 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2021.118056· OSTI ID:1960142

^[1]; Li, Yan ^[1]; ^[2]; Wu, Jianzhong ^[3]; ^[3]; Zhang, Yichen ^[4]; Xu, Tao ^[5]

Pennsylvania State University, University Park, PA (United States)
Temple University, Philadelphia, PA (United States)
Cardiff University, Wales (United Kingdom)
Argonne National Lab. (ANL), Lemont, IL (United States)
Tianjin University (China)

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Lemont, IL (United States)

Sponsoring Organization:: USDOE Office of Electricity

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1960142

Journal Information:: Applied Energy, Journal Name: Applied Energy Journal Issue: Part: B Vol. 306; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
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