A Decision Tree and S-transform based approach for power quality disturbances classification

Rodríguez, Alejandro; Merino, Erick; Aguado, José A.; López, Juan José Vaquero; Muñoz, Francisco Javier Pastor; Martín, Francisco; Naranjo, Javier

doi:10.1109/powereng.2013.6635763

Cited by 4 publications

(1 citation statement)

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“…Many such approaches classify power-system disturbances in the time domain. Decision trees were used to classify power-system disturbances in [14] and [15]. Statistical characteristics of power-system frequency were used in [16] to represent the signatures of power-system disturbances.…”

Section: Related Workmentioning

confidence: 99%

Classification of Disturbances and Cyber-Attacks in Power Systems Using Heterogeneous Time-Synchronized Data

Pan

Morris

Adhikari

2015

IEEE Trans. Ind. Inf.

128

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Visualization and situational awareness are of vital importance for power systems, as the earlier a power-system event such as a transmission line fault or cyber-attack is identified, the quicker operators can react to avoid unnecessary loss. Accurate time-synchronized data, such as system measurements and device status, provide benefits for system state monitoring. However, the time-domain analysis of such heterogeneous data to extract patterns is difficult due to the existence of transient phenomena in the analyzed measurement waveforms. This paper proposes a sequential pattern mining approach to accurately extract patterns of power-system disturbances and cyber-attacks from heterogeneous time-synchronized data, including synchrophasor measurements, relay logs, and network event monitor logs. The term common path is introduced. A common path is a sequence of critical system states in temporal order that represent individual types of disturbances and cyber-attacks. Common paths are unique signatures for each observed event type. They can be compared to observed system states for classification. In this paper, the process of automatically discovering common paths from labeled data logs is introduced. An included case study uses the common path-mining algorithm to learn common paths from a fusion of heterogeneous synchrophasor data and system logs for three types of disturbances (in terms of faults) and three types of cyber-attacks, which are similar to or mimic faults. The case study demonstrates the algorithm's effectiveness at identifying unique paths for each type of event and the accompanying classifier's ability to accurately discern each type of event.Index Terms-Common paths, cyber-attack detection, disturbances, symmetric and unsymmetrical faults, synchrophasor data and device log mining. 1551-3203

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Section: Related Workmentioning

confidence: 99%