Identifying harmonic attributes from online partial discharge data

Victoria Catterson; S. Bahadoorsingh; Susan Rudd; Stephen Mcarthur; S.M. Rowland

doi:10.1109/TPWRD.2011.2114373

Identifying harmonic attributes from online partial discharge data

Victoria Catterson, S. Bahadoorsingh, Susan Rudd, Stephen Mcarthur, S.M. Rowland

Electronic And Electrical Engineering

Research output: Contribution to journal › Article › peer-review

22 Citations (Scopus)

356 Downloads (Pure)

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.

Original language	English
Pages (from-to)	1811-1819
Number of pages	9
Journal	IEEE Transactions on Power Delivery
Volume	26
Issue number	3
DOIs	https://doi.org/10.1109/TPWRD.2011.2114373
Publication status	Published - Jul 2011

Keywords

discharges
harmonic analysis
insulation
monitoring
partial discharges

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10.1109/TPWRD.2011.2114373

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title = "Identifying harmonic attributes from online partial discharge data",

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.",

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author = "Victoria Catterson and S. Bahadoorsingh and Susan Rudd and Stephen Mcarthur and S.M. Rowland",

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AU - Catterson, Victoria

AU - Bahadoorsingh, S.

AU - Rudd, Susan

AU - Mcarthur, Stephen

AU - Rowland, S.M.

PY - 2011/7

Y1 - 2011/7

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AB - 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.

KW - discharges

KW - harmonic analysis

KW - insulation

KW - monitoring

KW - partial discharges

U2 - 10.1109/TPWRD.2011.2114373

DO - 10.1109/TPWRD.2011.2114373

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JO - IEEE Transactions on Power Delivery

JF - IEEE Transactions on Power Delivery

IS - 3

ER -

Identifying harmonic attributes from online partial discharge data

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Keywords

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