Utilizing Matrix Profile for Enhanced Detection of Events in Sampled Values

The merging units (MUs) serve as the critical interface between analog signals in power systems and digital instruments that process these data considering the IEC 61850 standards. Their primary function is to acquire digitized samples and transmit them to intelligent electronic devices for further processing. MUs are the first elements in the measurement chain capable of detecting events in the power system. In this context, this paper introduces an event identification function, to implement in the MUs, based on the matrix profile technique, which can effectively identify events such as voltage dips, even in noisy signal environments or when events overlap. The method can improve the reliability and accuracy of power quality monitoring and event detection in complex power system scenarios.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/amps62611.2024.10706669
Citations
3
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
1.04
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article

Utilizing Matrix Profile for Enhanced Detection of Events in Sampled Values

Guglielmo Frigo, Sara Sulis, Davide Sitzia, Paolo Castello
3 citations
Fuzzy Logic and Control Systems
1.04
article

Utilizing Matrix Profile for Enhanced Detection of Events in Sampled Values

Guglielmo Frigo, Sara Sulis, Davide Sitzia, Paolo Castello
article en
3 citations

Abstract

The merging units (MUs) serve as the critical interface between analog signals in power systems and digital instruments that process these data considering the IEC 61850 standards. Their primary function is to acquire digitized samples and transmit them to intelligent electronic devices for further processing. MUs are the first elements in the measurement chain capable of detecting events in the power system. In this context, this paper introduces an event identification function, to implement in the MUs, based on the matrix profile technique, which can effectively identify events such as voltage dips, even in noisy signal environments or when events overlap. The method can improve the reliability and accuracy of power quality monitoring and event detection in complex power system scenarios.

University of Cagliari (IT), Swiss Federal Institute of Metrology (CH)
Openalex Percentile: Top 19%
Fuzzy Logic and Control Systems
1.04
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Utilizing Matrix Profile for Enhanced Detection of Events in Sampled Values — Guglielmo Frigo, Sara Sulis, et al. · (2024) | TGRS Research Map | TGRS