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

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dc.contributor.author Velasco Rodríguez, José Ángel
dc.contributor.author Amarís Duarte, Hortensia Elena
dc.contributor.author Alonso Martínez, Mónica
dc.date.accessioned 2020-10-26T10:08:02Z
dc.date.available 2020-10-26T10:08:02Z
dc.date.issued 2020-10
dc.identifier.bibliographicCitation Velasco, 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, 106054
dc.identifier.issn 0142-0615
dc.identifier.uri http://hdl.handle.net/10016/31297
dc.description.abstract Distribution 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.
dc.description.sponsorship This 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).
dc.format.extent 16
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2020 The Authors.
dc.rights Atribución 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by/3.0/es/
dc.subject.other Smart Grids
dc.subject.other Deep learning
dc.subject.other Uncertainty
dc.subject.other Probabilistic modelling
dc.subject.other Clustering
dc.subject.other Phase imbalance
dc.title Deep Learning loss model for large-scale low voltage smart grids
dc.type article
dc.subject.eciencia Ingeniería Industrial
dc.identifier.doi https://doi.org/10.1016/j.ijepes.2020.106054
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. RTC-2014-1556-3
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 106054
dc.identifier.publicationtitle International Journal of Electrical Power & Energy Systems
dc.identifier.publicationvolume 121
dc.identifier.uxxi AR/0000026005
dc.contributor.funder Ministerio de Economía y Competitividad (España)
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