Automated recognition of irregularities in substation load profiles due to abnormal feeding arrangements

A J. Leaman; Hassan Nouri; Alexis Polycarpou; F. V. der Linde; Rade M. Ćirić

doi:10.1109/upec.2008.4651542

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Automated recognition of irregularities in substation load profiles due to abnormal feeding arrangements

A J. Leaman Hassan Nouri Alexis Polycarpou F. V. der Linde Rade M. Ćirić

Year: 2008 Pages: 1-5

DOI: 10.1109/upec.2008.4651542

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Abstract

Detection of abnormal feeding through the concept of data mining is studied. The presented results are in the form of case studies for various abnormalities. The developed detection algorithm is based on feeding patterns that compare the load profile against a reference waveform in conjunction with a threshold to denote abnormality.

Keywords:

Abnormality Waveform Computer science Conjunction (astronomy) Pattern recognition (psychology) Artificial intelligence Data mining Medicine Telecommunications

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Power Systems Fault Detection

Physical Sciences → Engineering → Control and Systems Engineering

Smart Grid and Power Systems

Physical Sciences → Engineering → Electrical and Electronic Engineering

Electric Power Systems and Control

Physical Sciences → Engineering → Electrical and Electronic Engineering

Automated recognition of irregularities in substation load profiles due to abnormal feeding arrangements

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