Data analytics to support operational distribution network monitoring

Research output: Contribution to conferencePaper

Abstract

The operation of distribution networks has become more challenging in recent years with increasing levels of embedded generation and other low carbon technologies pushing these towards their design limits. To identify the nature and extent of these challenges, network operators are deploying monitoring equipment on low voltage feeders, leading to new insights into fault behaviour and usage characterisation. With this heightened level of observability comes the additional challenge of finding models that translate raw data streams into outputs on which operational decisions can be based or supported. In this
paper, operational low voltage substation and feeder monitoring data from a UK distribution network is used to identify fault occurrence relations to localised meteorological data, characterise the localised network sensitivities of demand dynamics and infer the effects of embedded generation not visible to the network operator. These case studies are then used to show how additional operational context can be provided to the network operator through the application of analytics.

Conference

ConferenceIEEE PES Innovative Smart Grid Technologies Conference Europe 2018
Abbreviated titleISGT-E 2018
CountryBosnia and Herzegovina
CitySarajevo
Period21/10/1825/10/18
Internet address

Fingerprint

Electric power distribution
Monitoring
Observability
Electric potential
Carbon

Keywords

  • power system fault anticipation
  • distribution network monitoring
  • data analytics

Cite this

Tsioumpri, E., Stephen, B., Dunn-Birch, N., & McArthur, S. D. J. (2018). Data analytics to support operational distribution network monitoring. Paper presented at IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, Sarajevo, Bosnia and Herzegovina.
Tsioumpri, Eleni ; Stephen, Bruce ; Dunn-Birch, Neil ; McArthur, Stephen D.J. / Data analytics to support operational distribution network monitoring. Paper presented at IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, Sarajevo, Bosnia and Herzegovina.6 p.
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title = "Data analytics to support operational distribution network monitoring",
abstract = "The operation of distribution networks has become more challenging in recent years with increasing levels of embedded generation and other low carbon technologies pushing these towards their design limits. To identify the nature and extent of these challenges, network operators are deploying monitoring equipment on low voltage feeders, leading to new insights into fault behaviour and usage characterisation. With this heightened level of observability comes the additional challenge of finding models that translate raw data streams into outputs on which operational decisions can be based or supported. In thispaper, operational low voltage substation and feeder monitoring data from a UK distribution network is used to identify fault occurrence relations to localised meteorological data, characterise the localised network sensitivities of demand dynamics and infer the effects of embedded generation not visible to the network operator. These case studies are then used to show how additional operational context can be provided to the network operator through the application of analytics.",
keywords = "power system fault anticipation, distribution network monitoring, data analytics",
author = "Eleni Tsioumpri and Bruce Stephen and Neil Dunn-Birch and McArthur, {Stephen D.J.}",
year = "2018",
month = "10",
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language = "English",
note = "IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, ISGT-E 2018 ; Conference date: 21-10-2018 Through 25-10-2018",
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Tsioumpri, E, Stephen, B, Dunn-Birch, N & McArthur, SDJ 2018, 'Data analytics to support operational distribution network monitoring' Paper presented at IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, Sarajevo, Bosnia and Herzegovina, 21/10/18 - 25/10/18, .

Data analytics to support operational distribution network monitoring. / Tsioumpri, Eleni; Stephen, Bruce; Dunn-Birch, Neil; McArthur, Stephen D.J.

2018. Paper presented at IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, Sarajevo, Bosnia and Herzegovina.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Data analytics to support operational distribution network monitoring

AU - Tsioumpri, Eleni

AU - Stephen, Bruce

AU - Dunn-Birch, Neil

AU - McArthur, Stephen D.J.

PY - 2018/10/21

Y1 - 2018/10/21

N2 - The operation of distribution networks has become more challenging in recent years with increasing levels of embedded generation and other low carbon technologies pushing these towards their design limits. To identify the nature and extent of these challenges, network operators are deploying monitoring equipment on low voltage feeders, leading to new insights into fault behaviour and usage characterisation. With this heightened level of observability comes the additional challenge of finding models that translate raw data streams into outputs on which operational decisions can be based or supported. In thispaper, operational low voltage substation and feeder monitoring data from a UK distribution network is used to identify fault occurrence relations to localised meteorological data, characterise the localised network sensitivities of demand dynamics and infer the effects of embedded generation not visible to the network operator. These case studies are then used to show how additional operational context can be provided to the network operator through the application of analytics.

AB - The operation of distribution networks has become more challenging in recent years with increasing levels of embedded generation and other low carbon technologies pushing these towards their design limits. To identify the nature and extent of these challenges, network operators are deploying monitoring equipment on low voltage feeders, leading to new insights into fault behaviour and usage characterisation. With this heightened level of observability comes the additional challenge of finding models that translate raw data streams into outputs on which operational decisions can be based or supported. In thispaper, operational low voltage substation and feeder monitoring data from a UK distribution network is used to identify fault occurrence relations to localised meteorological data, characterise the localised network sensitivities of demand dynamics and infer the effects of embedded generation not visible to the network operator. These case studies are then used to show how additional operational context can be provided to the network operator through the application of analytics.

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KW - distribution network monitoring

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Tsioumpri E, Stephen B, Dunn-Birch N, McArthur SDJ. Data analytics to support operational distribution network monitoring. 2018. Paper presented at IEEE PES Innovative Smart Grid Technologies Conference Europe 2018, Sarajevo, Bosnia and Herzegovina.