Abstract
The power industry is in the process of grid modernization with the introduction of phasor measurement units (PMUs), advanced metering infrastructure (AMI), and other technologies. Although these technologies enable more reliable and efficient operation, the risk of cyber threats has increased, as evidenced by the recent blackouts in Ukraine and New York. One of these threats is false data injection attacks (FDIAs). Most of the FDIA literature focuses on the vulnerability of DC estimators and AC estimators to such attacks. This paper investigates FDIAs for PMU-based state estimation, where the PMUs are comparable. Several states can be manipulated by compromising one PMU through the channels of that PMU. A Phase Locking Value (PLV) technique was developed to detect FDIAs. The proposed approach is tested on the IEEE 14-bus and the IEEE 30-bus test systems under different scenarios using a Monte Carlo simulation where the PLV demonstrated an efficient performance.
Highlights
In recent years, numerous cyber-attacks were launched against electric power systems, which caused power outages, such as the Ukraine blackout on 23 December 2015 and Manhattan, New York blackout on 13 July 2019 [1,2]
We introduced phasor measurement units (PMUs)-based false data injection attacks (FDIAs) where compromising one PMU is sufficient to launch successful attacks and bypass bad data detection (BDD)
The paper introduces a new approach for detecting FDIA where Phase Locking Value (PLV) is used to measure the correlation between the measured signals and detect abnormalities
Summary
Numerous cyber-attacks were launched against electric power systems, which caused power outages, such as the Ukraine blackout on 23 December 2015 and Manhattan, New York blackout on 13 July 2019 [1,2]. The recent advancements of smart meters, such as phasor measurement units (PMUs) and advanced meter infrastructure (AMI), have enhanced the situational awareness and enabled a more secure grid operation Common among noise processes, it could be noticed that, with the introduction of noise, the PLV tends toward zero implying that the underlying signals deviate from being synchronized This motivated us to utilize this concept in the identification of FDIA, and we hypothesized that under normal circumstances, when there is no data manipulation, the buses in the grid will have consistent phase changes between them, whereas, in the case of manipulated data, the differences between phases will no longer be constant.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
