Spatio-Temporal Synchrophasor Data Characterization for Mitigating False Data Injection in Smart Grids

Cui, Yi; Wang, Weikang; Li, Fangxing; Fuhr, Peter L.; Morales-Rodríguez, Marissa E.

doi:10.1109/pesgm40551.2019.8973586

Cited by 12 publications

(9 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The shift of about 1 s in predictions that is observed on the top right of Figure 3 is due to the shape of the time series from the target's closest neighbor (see dotted dark blue curve in Figure 6). The covariance structure in (9) assumes that locations closer to each other have a higher correlation than those farther apart. In other words, the proposed models give more weight to the sites nearby and ignore the unobserved generator network from the correlation structure, which can be unsuitable for some instances, such as the southern Florida site.…”

Section: Analysis Of the Spatial Correlationmentioning

confidence: 99%

See 1 more Smart Citation

Power grid frequency prediction using spatiotemporal modeling

Lenzi

Bessac

Anitescu

2021

Statistical Analysis

View full text Add to dashboard Cite

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S.Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. The proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

show abstract

Section: Analysis Of the Spatial Correlationmentioning

confidence: 99%

“…Cyberattack effects on smart grids are usually mitigated by using techniques for reconstructing missing data [9,15,24]. Since the problem's spatial aspect is disregarded, such practices can restore only the data at monitored locations.…”

Section: Introductionmentioning

confidence: 99%

Power grid frequency prediction using spatiotemporal modeling

Lenzi

Bessac

Anitescu

2021

Statistical Analysis

View full text Add to dashboard Cite

show abstract

“…Such attacks can be performed either by shutting down the channel of communication or by sending false messages. Global positioning system (GPS) spoofing is a type of FDIA on the GPS signal transmitted to the device where the attacker produces the GPS signal and injects false data into it [84]. Other well‐known communications‐based attacks are message replay and relay threats.…”

Section: Cyber–physical Attack Scenariosmentioning

confidence: 99%

Cyber–physical security for on‐going smart grid initiatives: a survey

Hossain

Peng

2020

IET cyber-phys. syst.

View full text Add to dashboard Cite

The smart grid is an upgraded concept of electricity network with tight coupling among information, control, and bidirectional communication technologies. Along with the silent features of the ongoing smart grid, cyber-physical security appears to be a deep concern due to its significant dependence on sensing technologies, complex networks of computers, intelligence, and wide-area communication infrastructures. Moreover, the smart grid is an extensive critical infrastructure and vulnerable to coordinated cyber-physical attacks. As a result, cyber-physical attacks cause significant threats to the confidentiality and integrity of the power data, including power outages, cascading failures, and unnecessary expenditure. In this study, security issues of smart grid, including cyber-physical interdependency, attack varieties, detection methods, requirements, standards, challenges, and future prospects, are taken into consideration for both cyber and physical systems, aiming to provide an extensive understanding of vulnerabilities and solutions for the smart power grid. By revealing the inherent features of cyber-physical security in the smart grid, this survey study is addressed to facilitate future research in these two areas.

show abstract

“…Synchrophasor technology provides high‐resolution global positioning system (GPS) time‐synchronised phasor measurements [1–4]. It reveals unprecedented insights into power grid dynamics and is widely used in applications including disturbance detection, fault location, data mining, cybersecurity [5–12] etc.…”

Section: Introductionmentioning

confidence: 99%