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dc.contributor.authorForos, Jørn
dc.contributor.authorIstad, Maren
dc.contributor.authorMorch, Andrei
dc.contributor.authorMathisen, Bjørn Magnus
dc.date.accessioned2019-07-24T12:48:46Z
dc.date.available2019-07-24T12:48:46Z
dc.date.issued2019-06-03
dc.identifier.isbn978-2-9602415-0-1
dc.identifier.issn2032-9644
dc.identifier.urihttps://cired-repository.org/handle/20.500.12455/735
dc.identifier.urihttp://dx.doi.org/10.34890/959
dc.description.abstractThis paper discusses the use of machine learning (ML) techniques to improve fault handling in distribution networks. The paper includes a short survey on the use of ML techniques in fault handling and shows that little published work has been done on using weather data and smart metering data as data sources. It can be argued that this is desired to increase the performance and usability of ML in operational support systems. Previous work also focuses almost exclusively on statistical machine learning aiming to replace traditional simulation models, overlooking other ML methods which can support operations. Here it is illustrated that Case based reasoning (CBR) can be used to aid the decision-making for example, when trying to restore service after an outage. The paper also describes the use of experience databases to aid the operator during fault handling. To illustrate potential use of ML and CBR, the paper presents a use case for future fault handling in low voltage distribution network and discusses the usefulness of this approach. This example shows that implementation of ML techniques in daily operation can be expected to contribute to reduction of costs for the network companies and increased security of supply for the customers. 
dc.language.isoen
dc.publisherAIM
dc.relation.ispartofseriesCIRED Conference Proceedings
dc.titleUSE CASE APPLYING MACHINE-LEARNING TECHNIQUES FOR IMPROVING OPERATION OF THE DISTRIBUTION NETWORK
dc.typeConference Proceedings
dc.description.conferencelocationMadrid, Spain
dc.relation.ispartProc. of the 25th International Conference on Electricity Distribution (CIRED 2019)
dc.contributor.detailedauthorForos, Jørn, SINTEF Energy Research, Norway
dc.contributor.detailedauthorIstad, Maren, SINTEF Energy Research, Norway
dc.contributor.detailedauthorMorch, Andrei, SINTEF Energy Research, Norway
dc.contributor.detailedauthorMathisen, Bjørn Magnus, SINTEF Digital, Norway
dc.date.conferencedate3-6 June 2019
dc.description.peerreviewedYes
dc.title.number2114
dc.description.openaccessYes
dc.contributor.countryNorway
dc.contributor.countryNorway
dc.contributor.countryNorway
dc.contributor.countryNorway
dc.description.conferencenameCIRED 2019
dc.contributor.affiliationSINTEF Energy Research
dc.contributor.affiliationSINTEF Energy Research
dc.contributor.affiliationSINTEF Energy Research
dc.contributor.affiliationSINTEF Digital
dc.description.sessionOperation, control and protection
dc.description.sessionidSession 3


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