Incipient Equipment Failure Assessment and Avoidance through Robust Detection Technqiue

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Abstract

Key contributor to normal power grid operations is optimal working of the various power grid equipment/apparatus. Nonoptimal operation of any of this equipment causes power quality problems which can pose great risk to the stability of the grid. Damaged or partially damaged equipment leaves characteristic signatures in the form of current and voltage waveform distortions. Detecting and localizing such signal distortions would contribute to grid reliability as the damaged equipment could be replaced in time before it can cause further damage. This paper proposes a Distortion Detection Technique (DDT) based on second-difference approach. This distortion detection technique has very low memory requirements and can be easily implemented on decentralized systems. The paper investigates the performance of this technique and evaluates it with case studies involving different kind of equipment failures simulated on Real Time Digital Simulator (RTDS).

Original languageEnglish
Title of host publicationIET Conference Publications
PublisherIET
Number of pages6
EditionCP759
ISBN (Electronic)978-953-184-249-5
ISBN (Print)9781785617911, 9781839531330
DOIs
Publication statusPublished - 2019
Event11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion - Dubrovnik, Croatia
Duration: 12 Nov 201815 Nov 2018
http://medpower2018.com/

Publication series

NameIET Conference Publications
NumberCP759
Volume2018

Conference

Conference11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion
Abbreviated titleMEDPOWER 2018
CountryCroatia
CityDubrovnik
Period12/11/1815/11/18
Internet address

Keywords

  • Condition Based Maintenance
  • Distortion Detection
  • Equipment Failure
  • Power System Reliability
  • Waveform Analytics

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