Mostrar el registro sencillo del ítem

dc.contributor.authorGómez de la Varga, J.
dc.contributor.authorPineda-Morente, Salvador 
dc.contributor.authorMorales-González, Juan Miguel 
dc.contributor.authorPorras, Álvaro
dc.date.accessioned2024-07-10T11:19:57Z
dc.date.available2024-07-10T11:19:57Z
dc.date.issued2024-01
dc.identifier.urihttps://hdl.handle.net/10630/32039
dc.description.abstractThe task of state estimation in active distribution systems faces a major challenge due to the integration of different measurements with multiple reporting rates. As a result, distribution systems are essentially unobservable in real time, indicating the existence of multiple states that result in identical values for the available measurements. Certain existing approaches utilize historical data to infer the relationship between real-time available measurements and the state. Other learning-based methods aim to estimate the measurements acquired with a delay, generating pseudo-measurements. Our paper presents a methodology that utilizes the outcome of an unobservable state estimator to exploit information on the joint probability distribution between real-time available measurements and delayed ones. Through numerical simulations conducted on a realistic distribution grid with insufficient real-time measurements, the proposed procedure showcases superior performance compared to existing state forecasting approaches and those relying on inferred pseudo-measurements.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Teches_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAprendizaje automáticoes_ES
dc.subject.otherReal-time observabilityes_ES
dc.subject.otherActive distribution networkses_ES
dc.subject.otherMachine learninges_ES
dc.subject.otherPseudo-measurementses_ES
dc.subject.otherState estimationes_ES
dc.titleLearning-based State Estimation in Distribution Systems with Limited Real-Time Measurements.es_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroEscuela de Ingenierías Industrialeses_ES
dc.relation.eventtitle33rd European Conference on Operational Researches_ES
dc.relation.eventplaceCopenhagen, Denmarkes_ES
dc.relation.eventdate30/06/2024es_ES
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*


Ficheros en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional