Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment

This paper addresses the customer-phase identification problem in three-phase distribution grids including three-phase customers characterized by aggregated energy measurements. The proposed technique first solves a relaxed problem, in which the binary nature of the variables is ignored, which leads...

Descripción completa

Detalles Bibliográficos
Autores: González Cagigal, Miguel Ángel, Rosendo Macías, José Antonio, Gómez Expósito, Antonio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/137529
Acceso en línea:https://hdl.handle.net/11441/137529
https://doi.org/10.1016/j.ijepes.2022.108445
Access Level:acceso abierto
Palabra clave:Constrained least squares
Gaussian distribution
Phase identification
Smart metering
Distribution grid
id ES_331a2b9060511bbb5cf22ecfd83ca098
oai_identifier_str oai:idus.us.es:11441/137529
network_acronym_str ES
network_name_str España
repository_id_str
spelling Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignmentGonzález Cagigal, Miguel ÁngelRosendo Macías, José AntonioGómez Expósito, AntonioConstrained least squaresGaussian distributionPhase identificationSmart meteringDistribution gridThis paper addresses the customer-phase identification problem in three-phase distribution grids including three-phase customers characterized by aggregated energy measurements. The proposed technique first solves a relaxed problem, in which the binary nature of the variables is ignored, which leads to a constrained, least-squares estimation, using as inputs the active and reactive energy readings provided by the smart meters, along with the energy delivered by each phase at the head of the feeder. With the estimated values of the decision variables, and their corresponding variances, a confidence-based selection technique is then applied for the sequential assignment of the customer with the highest joint probability of being connected to one of the three phases but not to the other two. The performance of the proposed procedure is assessed with five different scenarios in terms of accuracy for increasing number of loads and measurement errors. The robustness of the algorithm is additionally tested in the presence of model errors, and its performance is compared to that of existing methods.Project Solar to Vehicle (S2V) INV-3-2021-I-038Research project HySGrid+ CER-20191019ElsevierIngeniería EléctricaTEP196: Sistemas de Energía Eléctrica2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/137529https://doi.org/10.1016/j.ijepes.2022.108445reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésInternational Journal of Electrical Power & Energy Systems, 143, 108445.INV-3-2021-I-038CER-20191019https://www.sciencedirect.com/science/article/pii/S0142061522004550info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1375292026-06-17T12:51:07Z
dc.title.none.fl_str_mv Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
title Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
spellingShingle Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
González Cagigal, Miguel Ángel
Constrained least squares
Gaussian distribution
Phase identification
Smart metering
Distribution grid
title_short Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
title_full Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
title_fullStr Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
title_full_unstemmed Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
title_sort Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment
dc.creator.none.fl_str_mv González Cagigal, Miguel Ángel
Rosendo Macías, José Antonio
Gómez Expósito, Antonio
author González Cagigal, Miguel Ángel
author_facet González Cagigal, Miguel Ángel
Rosendo Macías, José Antonio
Gómez Expósito, Antonio
author_role author
author2 Rosendo Macías, José Antonio
Gómez Expósito, Antonio
author2_role author
author
dc.contributor.none.fl_str_mv Ingeniería Eléctrica
TEP196: Sistemas de Energía Eléctrica
dc.subject.none.fl_str_mv Constrained least squares
Gaussian distribution
Phase identification
Smart metering
Distribution grid
topic Constrained least squares
Gaussian distribution
Phase identification
Smart metering
Distribution grid
description This paper addresses the customer-phase identification problem in three-phase distribution grids including three-phase customers characterized by aggregated energy measurements. The proposed technique first solves a relaxed problem, in which the binary nature of the variables is ignored, which leads to a constrained, least-squares estimation, using as inputs the active and reactive energy readings provided by the smart meters, along with the energy delivered by each phase at the head of the feeder. With the estimated values of the decision variables, and their corresponding variances, a confidence-based selection technique is then applied for the sequential assignment of the customer with the highest joint probability of being connected to one of the three phases but not to the other two. The performance of the proposed procedure is assessed with five different scenarios in terms of accuracy for increasing number of loads and measurement errors. The robustness of the algorithm is additionally tested in the presence of model errors, and its performance is compared to that of existing methods.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/137529
https://doi.org/10.1016/j.ijepes.2022.108445
url https://hdl.handle.net/11441/137529
https://doi.org/10.1016/j.ijepes.2022.108445
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Journal of Electrical Power & Energy Systems, 143, 108445.
INV-3-2021-I-038
CER-20191019
https://www.sciencedirect.com/science/article/pii/S0142061522004550
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869405725099294720
score 15,300719

Similares en LA Referencia