2023
DOI: 10.3390/en16186678
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Anomaly Detection in Power System State Estimation: Review and New Directions

Austin Cooper,
Arturo Bretas,
Sean Meyn

Abstract: Foundational and state-of-the-art anomaly-detection methods through power system state estimation are reviewed. Traditional components for bad data detection, such as chi-square testing, residual-based methods, and hypothesis testing, are discussed to explain the motivations for recent anomaly-detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest-change detection and artific… Show more

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Cited by 2 publications
(2 citation statements)
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“…The current state estimation considers the circuit breaker currents as states in the LSE. Based on Kirchhoff's Current Law (KCL), the relationship between the circuit breaker current and the injection currents in the zero impedance network can be written as (4). z inj refers to the current injection by each node, and A breaker is the adjacent matrix that defines the relationship, which is the node connectivity matrix (NCM) of the H-TNTP Level 2. r inj is the injection current measurement residue.…”
Section: Substation Levelmentioning
confidence: 99%
See 1 more Smart Citation
“…The current state estimation considers the circuit breaker currents as states in the LSE. Based on Kirchhoff's Current Law (KCL), the relationship between the circuit breaker current and the injection currents in the zero impedance network can be written as (4). z inj refers to the current injection by each node, and A breaker is the adjacent matrix that defines the relationship, which is the node connectivity matrix (NCM) of the H-TNTP Level 2. r inj is the injection current measurement residue.…”
Section: Substation Levelmentioning
confidence: 99%
“…Traditional state estimation was introduced to the power system by Fred Schweppe in 1970 in [1][2][3] to process available imperfect information (noise, bad data, or false data) [4,5] and produces the best possible estimates for the state variables in consideration. However, the traditional static state estimation is inefficient in estimating state variables in modern power systems.…”
Section: Introductionmentioning
confidence: 99%