Show simple item record

dc.contributor.authorHayes, Barry P.
dc.contributor.authorGruber, Jorn K.
dc.contributor.authorProdanovic, Milan
dc.date.accessioned2018-06-19T14:12:03Z
dc.date.available2018-06-19T14:12:03Z
dc.date.issued2018-06-10
dc.identifier.citationHayes, Barry P., Gruber, Jorn K., & Prodanovic, Milan. (2018). Multi-nodal short-term energy forecasting using smart meter data. IET Generation, Transmission and Distribution, 12(12), 2988-2994, Doi:10.1049/iet-gtd.2017.1599en_IE
dc.identifier.issn1751-8695
dc.identifier.urihttp://hdl.handle.net/10379/7403
dc.description.abstractThis paper deals with the short-term forecasting of electrical energy demands at the local level, incorporating advanced metering infrastructure (AMI), or ‘smart meter’ data. It provides a study of the effects of aggregation on electrical energy demand modelling and multi-nodal demand forecasting. This paper then presents a detailed assessment of the variables which affect electrical energy demand, and how these effects vary at different levels of demand aggregation. Finally, this study outlines an approach for incorporating AMI data in short-term forecasting at the local level, in order to improve forecasting accuracy for applications in distributed energy systems, microgrids and transactive energy. The analysis presented in this study is carried out using large AMI data sets comprised of recorded demand and local weather data from test sites in two European countries.en_IE
dc.description.sponsorshipThe authors kindly acknowledge the support of the European Commission provided through the Marie Curie researcher mobility action (FP7-PEOPLE-2013-COFUND), and the SmartHG research project (FP7-ICT-2011-8).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherInstitution of Engineering and Technology (IET)en_IE
dc.relation.ispartofIet Generation Transmission & Distributionen
dc.subjectDistributed power generationen_IE
dc.subjectLoad forecastingen_IE
dc.subjectSmart metersen_IE
dc.subjectElectrical energy demand modellingen_IE
dc.subjectTransactive energyen_IE
dc.subjectAMIen_IE
dc.subjectMultinodal demand forecastingen_IE
dc.subjectDistributed energy systemen_IE
dc.subjectSmart meter dataen_IE
dc.subjectAdvanced metering infrastructureen_IE
dc.subjectEuropean countryen_IE
dc.subjectMicrogriden_IE
dc.subjectMultinodal short-term energy forecastingen_IE
dc.titleMulti-nodal short-term energy forecasting using smart meter dataen_IE
dc.typeArticleen_IE
dc.date.updated2018-06-15T11:10:13Z
dc.identifier.doi10.1049/iet-gtd.2017.1599
dc.local.publishedsourcehttps://dx.doi.org/10.1049/iet-gtd.2017.1599en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderSeventh Framework Programmeen_IE
dc.contributor.funderFP7 People: Marie-Curie Actionsen_IE
dc.internal.rssid14486576
dc.local.contactBarry Hayes. Email: barry.hayes@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
nui.item.downloads239


Files in this item

Attribution-NonCommercial-NoDerivs 3.0 Ireland
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. Please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.

The following license files are associated with this item:

Thumbnail

This item appears in the following Collection(s)

Show simple item record