An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TSG.2022.3144606 http://hdl.handle.net/11449/223314 |
Resumo: | Nonintrusive Load Monitoring (NILM) is the process to disaggregate the power consumption in appliances using a single meter installed on the residence electric entrance. We introduce a novel load modeling approach for power consumption disaggregation using the equivalent circuit concept from the Conservative Power Theory (CPT). CPT can represent an appliance or an operation stage using an equivalent circuit based on load parameters. This method allows obtaining load disaggregation models efficiently, easily, and fast, without requiring to collect and label plenty of samples. To validate it, we have (i) used a meter to capture signals from the aggregate consumption; (ii) extracted the features from the CPT equivalent circuit parameters for appliance recognition in a load event; (iii) created and validated a classifier constructed through equivalent circuits of the appliances, and (iv) tested the classifier in NILM real-world case studies. Experiments from different appliances achieved promising results, indicating effective load disaggregation capacity and reinforcing CPT as groundwork for load characterization towards an efficient load disaggregation. |
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Repositório Institucional da UNESP |
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An Effective CPT-based Nonintrusive Load Monitoring for Cognitive MetersCPT.equivalent circuitEquivalent circuitsHarmonic analysisIntegrated circuit modelingload disaggregationLoad modelingLoad monitoringNonintrusive load monitoringVoltageVoltage measurementNonintrusive Load Monitoring (NILM) is the process to disaggregate the power consumption in appliances using a single meter installed on the residence electric entrance. We introduce a novel load modeling approach for power consumption disaggregation using the equivalent circuit concept from the Conservative Power Theory (CPT). CPT can represent an appliance or an operation stage using an equivalent circuit based on load parameters. This method allows obtaining load disaggregation models efficiently, easily, and fast, without requiring to collect and label plenty of samples. To validate it, we have (i) used a meter to capture signals from the aggregate consumption; (ii) extracted the features from the CPT equivalent circuit parameters for appliance recognition in a load event; (iii) created and validated a classifier constructed through equivalent circuits of the appliances, and (iv) tested the classifier in NILM real-world case studies. Experiments from different appliances achieved promising results, indicating effective load disaggregation capacity and reinforcing CPT as groundwork for load characterization towards an efficient load disaggregation.Department of Electrical Engineering, Federal University of Technology, Paraná, Cornélio Procópio, PR, 86300-000, Brazil. (e-mail: wesley.angelino@unesp.br)Department of Computer Science, Federal University of São Carlos, Sorocaba, SP, 18052-780, Brazil.Universidade Estadual Paulista (UNESP)Souza, Wesley AAlmeida, Tiago A2022-04-28T19:49:59Z2022-04-28T19:49:59Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TSG.2022.3144606IEEE Transactions on Smart Grid.1949-30611949-3053http://hdl.handle.net/11449/22331410.1109/TSG.2022.31446062-s2.0-85123349052Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Transactions on Smart Gridinfo:eu-repo/semantics/openAccess2022-04-28T19:49:59Zoai:repositorio.unesp.br:11449/223314Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:58:45.628126Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
title |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
spellingShingle |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters Souza, Wesley A CPT. equivalent circuit Equivalent circuits Harmonic analysis Integrated circuit modeling load disaggregation Load modeling Load monitoring Nonintrusive load monitoring Voltage Voltage measurement |
title_short |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
title_full |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
title_fullStr |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
title_full_unstemmed |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
title_sort |
An Effective CPT-based Nonintrusive Load Monitoring for Cognitive Meters |
author |
Souza, Wesley A |
author_facet |
Souza, Wesley A Almeida, Tiago A |
author_role |
author |
author2 |
Almeida, Tiago A |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Souza, Wesley A Almeida, Tiago A |
dc.subject.por.fl_str_mv |
CPT. equivalent circuit Equivalent circuits Harmonic analysis Integrated circuit modeling load disaggregation Load modeling Load monitoring Nonintrusive load monitoring Voltage Voltage measurement |
topic |
CPT. equivalent circuit Equivalent circuits Harmonic analysis Integrated circuit modeling load disaggregation Load modeling Load monitoring Nonintrusive load monitoring Voltage Voltage measurement |
description |
Nonintrusive Load Monitoring (NILM) is the process to disaggregate the power consumption in appliances using a single meter installed on the residence electric entrance. We introduce a novel load modeling approach for power consumption disaggregation using the equivalent circuit concept from the Conservative Power Theory (CPT). CPT can represent an appliance or an operation stage using an equivalent circuit based on load parameters. This method allows obtaining load disaggregation models efficiently, easily, and fast, without requiring to collect and label plenty of samples. To validate it, we have (i) used a meter to capture signals from the aggregate consumption; (ii) extracted the features from the CPT equivalent circuit parameters for appliance recognition in a load event; (iii) created and validated a classifier constructed through equivalent circuits of the appliances, and (iv) tested the classifier in NILM real-world case studies. Experiments from different appliances achieved promising results, indicating effective load disaggregation capacity and reinforcing CPT as groundwork for load characterization towards an efficient load disaggregation. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:49:59Z 2022-04-28T19:49:59Z 2022-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/TSG.2022.3144606 IEEE Transactions on Smart Grid. 1949-3061 1949-3053 http://hdl.handle.net/11449/223314 10.1109/TSG.2022.3144606 2-s2.0-85123349052 |
url |
http://dx.doi.org/10.1109/TSG.2022.3144606 http://hdl.handle.net/11449/223314 |
identifier_str_mv |
IEEE Transactions on Smart Grid. 1949-3061 1949-3053 10.1109/TSG.2022.3144606 2-s2.0-85123349052 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
IEEE Transactions on Smart Grid |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128881414111232 |