Decentralized Anomaly Identification in Cyber-Physical DC Microgrids
In IEEE Energy Conversion Congress and Exposition, 2022
Abstract
DC microgrids with distributed control architec-tures enhance the operational reliability, scalability and flexibility. However, the underlying communication infrastucture makes the system highly susceptible to cyber attacks. These attacks in DC microgrids cause severe impact, that can be easily misinterpreted as faults, which can then maloperate the protection decision. Although various protection schemes have been established, a tailor-made scheme to distinguish faults from cyber attacks is needed to ensure reliability of supply. In this paper, we use a two dimensional plane with deviation of current (§I) and voltage (§V) at the terminal of each converter to distinguish between cyber attacks and faults in DC microgrids. As this scheme is governed based on physics of secondary controller operation, it is simple to implement and scalable to any physical topology. The performance of the proposed scheme is tested with real time simulation in OPAL-RT environment with HYPERSIM software for different topologies including radial, ring and mesh networks. In addition, the scheme is also tested and verified for simultane-ous cyber attack on multiple converters. The simulation results validates that the proposed decentralized scheme is effective in both detecting and localizing cyber-physical anomalies within 2 ms.
Info
Conference Paper, 2022
In IEEE Energy Conversion Congress and Exposition, 2022
UN SDG Classification
DK Main Research Area
Science/Technology
