• DocumentCode
    1480557
  • Title

    Identifying Harmonic Attributes From Online Partial Discharge Data

  • Author

    Catterson, Victoria M. ; Bahadoorsingh, Sanjay ; Rudd, Susan ; McArthur, Stephen D J ; Rowland, Simon M.

  • Author_Institution
    Inst. for Energy & Environ., Univ. of Strathclyde, Glasgow, UK
  • Volume
    26
  • Issue
    3
  • fYear
    2011
  • fDate
    7/1/2011 12:00:00 AM
  • Firstpage
    1811
  • Lastpage
    1819
  • Abstract
    Partial discharge (PD) monitoring is a key method of tracking fault progression and degradation of insulation systems. Recent research discovered that the harmonic regime experienced by the plant also affects the PD pattern, questioning the conclusions about equipment health drawn from PD data. This paper presents the design and creation of an online system for harmonic circumstance monitoring of distribution cables, using only PD data. Based on machine learning techniques, the system can assess the prevalence of the 5th and 7th harmonic orders over the monitoring period. This information is key for asset managers to draw correct conclusions about the remaining life of polymeric cable insulation, and prevent overestimation of the degradation trend.
  • Keywords
    learning (artificial intelligence); partial discharges; power cable insulation; power engineering computing; power system faults; power system harmonics; power system measurement; PD pattern; distribution cables; fault progression tracking; harmonic attribute identification; harmonic circumstance monitoring; insulation system degradation; machine learning techniques; online partial discharge data; partial discharge monitoring; polymeric cable insulation; Discharges; Harmonic analysis; Insulation; Monitoring; Partial discharges; Power system harmonics; Training; Dielectric breakdown; epoxy resin insulation; monitoring; partial discharge (PD); power quality (PQ); power system harmonics;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2011.2114373
  • Filename
    5738708