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dc.contributor.authorKanazawa, Yuki
dc.contributor.authorIshikawa, Hiroyuki
dc.contributor.authorUenishi, Hirokazu
dc.contributor.authorIchinomiya, Hiroki
dc.date.accessioned2019-07-24T12:37:37Z
dc.date.available2019-07-24T12:37:37Z
dc.date.issuedJune 2019
dc.identifier.isbn978-2-9602415-0-1
dc.identifier.issn2032-9644
dc.identifier.urihttps://cired-repository.org/handle/20.500.12455/155
dc.description.abstractMaximum current is necessary to be estimated when designing a LV distribution grid, i.e. MV/LV pole-mounted transformers and LV feeders, which supplies customers of several in minimum and dozens in maximum. This is currently estimated from the total contract capacities of the customers supplied by the grid, multiplying diversity and demand factor corresponding to the number of customers. This method is rather efficient and simple because the calculation can be done simply by using the contract capacities and the numbers of contracts.However, there are some constraints in this method. Diversity and demand factors may not be correct as they were derived statistically from sampled current measurements of customers. Additionally, this research was carried out years ago and have never been updated as it takes vast time and effort to re-measure them. As a result, these factors may be out-of-date as recent changes in electricity usage are not taken into consideration, such as the introduction of highly-efficient appliances or the diversities in lifestyles of customers. Thus, there is a possibility that the current estimated from the conventional method which is used for designing the grid diverge much from the actual state. This leads to over investment.This paper describes our new methodology for estimating the load curves of newly-connected customers based on the off-line information, such as contract capacity, contract types, location of the customer, presence of PV, etc.
dc.language.isoen
dc.publisherAIM
dc.relation.ispartofseriesCIRED Conference Proceedings
dc.titleForecasting Method of LV Distribution’s Load CurveBy Means of Machine Learning Utilizing Smart Meter Data
dc.typeConference Proceedings
dc.description.conferencelocationMadrid, Spain
dc.relation.ispartProc. of the 25th International Conference on Electricity Distribution (CIRED 2019)
dc.contributor.detailedauthorKanazawa, Yuki, Chubu Electric Power Company, Japan
dc.contributor.detailedauthorIshikawa, Hiroyuki, Chubu Electric Power Company, Japan
dc.contributor.detailedauthorUenishi, Hirokazu, Chubu Electric Power Company, Japan
dc.contributor.detailedauthorIchinomiya, Hiroki, Mitsubishi Research Institute, Japan
dc.date.conferencedate3-6 June 2019
dc.description.peerreviewedYes
dc.title.number806
dc.description.openaccessYes
dc.contributor.countryJapan
dc.contributor.countryJapan
dc.contributor.countryJapan
dc.contributor.countryJapan
dc.description.conferencenameCIRED 2019
dc.contributor.affiliationChubu Electric Power Company
dc.contributor.affiliationChubu Electric Power Company
dc.contributor.affiliationChubu Electric Power Company
dc.contributor.affiliationMitsubishi Research Institute
dc.description.sessionOperation, control and protection
dc.description.sessionidSession 3


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