Publication:
Deep Learning loss model for large-scale low voltage smart grids

dc.affiliation.dptoUC3M. Departamento de Ingeniería Eléctricaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Redes y Sistemas de Energía Eléctrica (REDES)es
dc.contributor.authorVelasco Rodríguez, José Ángel
dc.contributor.authorAmarís Duarte, Hortensia Elena
dc.contributor.authorAlonso Martínez, Mónica
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2020-10-26T10:08:02Z
dc.date.available2020-10-26T10:08:02Z
dc.date.issued2020-10
dc.description.abstractDistribution systems operators (DSOs) encounter the challenge of managing network losses in large geographical areas with hundreds of secondary substations and thousands of customers and with an ever-increasing presence of renewable energy sources. This situation complicates the estimation process of power loss, which is paramount to improve the network energy efficiency level in the context of the European Union energy policies. Thus, this article presents a methodology to estimate power losses in large-scale low voltage (LV) smart grids. The methodology is based on a deep-learning loss model to infer the network technical losses considering a large rollout of smart meters, a high penetration of distributed generation (DG) and unbalanced operation, among other network characteristics. The methodology has been validated in a large-scale LV distribution area in Madrid (Spain). The proposed methodology has proven to be a potential network loss estimation tool to improve the energy efficiency level in large-scale smart grids with a high penetration of distributed resources. The accuracy of the proposed methodology outperforms that of the state-of-the-art loss estimation methods, exhibiting a rapid convergence which allows for its use in real-time operations.en
dc.description.sponsorshipThis work has been partly funded by the Spanish Ministry of Economy and Competitiveness through the National Program for Research Aimed at the Challenges of Society under the project OSIRIS (RTC-2014-1556-3).en
dc.format.extent16
dc.identifier.bibliographicCitationVelasco, J.A.; Amaris, H.; Alonso, M. (2020). Deep Learning loss model for large-scale low voltage smart grids. International Journal of Electrical Power & Energy Systems, 121, 106054en
dc.identifier.doihttps://doi.org/10.1016/j.ijepes.2020.106054
dc.identifier.issn0142-0615
dc.identifier.publicationfirstpage106054e
dc.identifier.publicationtitleInternational Journal of Electrical Power & Energy Systemsen
dc.identifier.publicationvolume121
dc.identifier.urihttps://hdl.handle.net/10016/31297
dc.identifier.uxxiAR/0000026005
dc.language.isoeng
dc.publisherElsevieren
dc.relation.projectIDGobierno de España. RTC-2014-1556-3
dc.rights© 2020 The Authors.en
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.ecienciaIngeniería Industriales
dc.subject.otherSmart Gridsen
dc.subject.otherDeep learningen
dc.subject.otherUncertaintyen
dc.subject.otherProbabilistic modellingen
dc.subject.otherClusteringen
dc.subject.otherPhase imbalanceen
dc.titleDeep Learning loss model for large-scale low voltage smart gridsen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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