Home energy management systems with branch-and-bound model-based predictive control techniques
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.1/17200 |
Resumo: | At a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature. |
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Home energy management systems with branch-and-bound model-based predictive control techniquesSistemas de gerenciamento de energia residencial com técnicas de controle preditivo baseadas em modelos baseados em ramificações e vinculadasHome energy management systemsBuilding energyModel-based predictive controlBranch-and-bound algorithmSensitivity analysisPhotovoltaicsBatteryAt a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature.72581/2020MDPISapientiaBot, KarolHabou Laouali, InoussaRuano, AntonioRuano, Maria2021-10-07T14:58:20Z2021-092021-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/17200eng10.3390/en141858521996-1073info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-09T02:01:14Zoai:sapientia.ualg.pt:10400.1/17200Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:07:12.994686Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Home energy management systems with branch-and-bound model-based predictive control techniques Sistemas de gerenciamento de energia residencial com técnicas de controle preditivo baseadas em modelos baseados em ramificações e vinculadas |
title |
Home energy management systems with branch-and-bound model-based predictive control techniques |
spellingShingle |
Home energy management systems with branch-and-bound model-based predictive control techniques Bot, Karol Home energy management systems Building energy Model-based predictive control Branch-and-bound algorithm Sensitivity analysis Photovoltaics Battery |
title_short |
Home energy management systems with branch-and-bound model-based predictive control techniques |
title_full |
Home energy management systems with branch-and-bound model-based predictive control techniques |
title_fullStr |
Home energy management systems with branch-and-bound model-based predictive control techniques |
title_full_unstemmed |
Home energy management systems with branch-and-bound model-based predictive control techniques |
title_sort |
Home energy management systems with branch-and-bound model-based predictive control techniques |
author |
Bot, Karol |
author_facet |
Bot, Karol Habou Laouali, Inoussa Ruano, Antonio Ruano, Maria |
author_role |
author |
author2 |
Habou Laouali, Inoussa Ruano, Antonio Ruano, Maria |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Sapientia |
dc.contributor.author.fl_str_mv |
Bot, Karol Habou Laouali, Inoussa Ruano, Antonio Ruano, Maria |
dc.subject.por.fl_str_mv |
Home energy management systems Building energy Model-based predictive control Branch-and-bound algorithm Sensitivity analysis Photovoltaics Battery |
topic |
Home energy management systems Building energy Model-based predictive control Branch-and-bound algorithm Sensitivity analysis Photovoltaics Battery |
description |
At a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-07T14:58:20Z 2021-09 2021-09-01T00:00:00Z |
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://hdl.handle.net/10400.1/17200 |
url |
http://hdl.handle.net/10400.1/17200 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.3390/en14185852 1996-1073 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799133316603969536 |