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Condition monitoring and prognostic indicators for network reliability

Condition monitoring and prognostic indicators for network reliability
Condition monitoring and prognostic indicators for network reliability
Large-scale investment in transmission and distribution networks are planned over the next 10-15 years to meet future demand and changes in power generation. However, it is important that existing assets continue to operate reliably and their health maintained. A research project is considering the increased use of simulation models that could provide accurate prognostics, targeting maintenance and reduce in service failures. Such models could be further refined with parameters obtained from on-line measurements at the asset. It is also important to consider the future development of the research agenda for condition monitoring of power networks and with colleagues from National Grid, PPA Energy and the Universities of Manchester and Strathclyde, the research team are preparing a Position Paper on this subject.
Christou, S.
aa6be8f1-94a8-469c-84b1-ac90fcbf4a46
Steele-Davies, J.
596de209-13d5-47d6-8ed1-7d613f08d363
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Swingler, S.G.
4f13fbb2-7d2e-480a-8687-acea6a4ed735
Christou, S.
aa6be8f1-94a8-469c-84b1-ac90fcbf4a46
Steele-Davies, J.
596de209-13d5-47d6-8ed1-7d613f08d363
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Swingler, S.G.
4f13fbb2-7d2e-480a-8687-acea6a4ed735

Christou, S., Steele-Davies, J., Lewin, P.L. and Swingler, S.G. (2012) Condition monitoring and prognostic indicators for network reliability. HubNet Smart Grids Symposium, United Kingdom. 11 - 12 Sep 2012. 1 pp .

Record type: Conference or Workshop Item (Poster)

Abstract

Large-scale investment in transmission and distribution networks are planned over the next 10-15 years to meet future demand and changes in power generation. However, it is important that existing assets continue to operate reliably and their health maintained. A research project is considering the increased use of simulation models that could provide accurate prognostics, targeting maintenance and reduce in service failures. Such models could be further refined with parameters obtained from on-line measurements at the asset. It is also important to consider the future development of the research agenda for condition monitoring of power networks and with colleagues from National Grid, PPA Energy and the Universities of Manchester and Strathclyde, the research team are preparing a Position Paper on this subject.

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More information

e-pub ahead of print date: September 2012
Published date: 14 September 2012
Venue - Dates: HubNet Smart Grids Symposium, United Kingdom, 2012-09-11 - 2012-09-12
Organisations: EEE

Identifiers

Local EPrints ID: 342860
URI: https://eprints.soton.ac.uk/id/eprint/342860
PURE UUID: a5110fec-fdab-4386-bfb4-a924e9f4d25d

Catalogue record

Date deposited: 18 Sep 2012 13:39
Last modified: 18 Jul 2017 05:26

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