Learning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security

Learning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security

TitleLearning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security
Publication TypeJournal Article
Year of Publication2020
AuthorsCiaran Roberts, Anna Scaglione, Mahdi Jamei, Reinhard Gentz, Sean Peisert, Emma M Stewart, Chuck McParland, Alex McEachern, Daniel Arnold
JournalIEEE Transactions on Smart Grid
Volume11
Issue1
Pagination749 - 761
Date Published01/2020
ISSN1949-3053
Abstract

Conventional cyber-security intrusion detection systems monitor network traffic for malicious activity and indications that an adversary has gained access to the system. The approach discussed here expands the idea of a traditional intrusion detection system within electrical power systems, specifically power distribution networks, by monitoring the physical behavior of the grid. This is achieved through the use of high-rate distribution Phasor Measurement Units (PMUs), alongside SCADA packets analysis, for the purpose of monitoring the behavior of discrete control devices. In this work we present a set of algorithms for passively learning the control logic of voltage regulators and switched capacitor banks. Upon detection of an abnormal operation, the operator is alerted and further action can be taken. The proposed learning algorithms are validated on both simulated data and on measured PMU data from a utility pilot deployment site.

DOI10.1109/TSG.2019.2936016
Short TitleIEEE Trans. Smart Grid
Refereed DesignationRefereed