Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting

Detalhes bibliográficos
Autor(a) principal: Neves-Silva, Rui
Data de Publicação: 2022
Outros Autores: Camarinha-Matos, Luis M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/145918
Resumo: Publisher Copyright: © 2022 by the authors.
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network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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spelling Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofittingbuildings industrydecision-support systemsenergy efficiencyhuman-factorsimulationComputer Science (miscellaneous)Geography, Planning and DevelopmentRenewable Energy, Sustainability and the EnvironmentBuilding and ConstructionEnvironmental Science (miscellaneous)Energy Engineering and Power TechnologyHardware and ArchitectureComputer Networks and CommunicationsManagement, Monitoring, Policy and LawSDG 7 - Affordable and Clean EnergyPublisher Copyright: © 2022 by the authors.The implementation of building retrofitting processes targeting higher energy efficiency is greatly influenced by the investor’s expectations regarding the return on investment. The baseline of this work is the assumption that it is possible to improve the predictability of the post-retrofit scenario, both in energy and financial terms, using data gathered on how a building is being used by its occupants. The proposed approach relies on simulation to estimate the impact of available energy-efficient solutions on future energy consumption, using actual usage data. Data on building usage are collected by a wireless sensor network, installed in the building for a minimum period that is established by the methodology. The energy simulation of several alternative retrofit scenarios is then the basis for the decision support process to help the investor directing the financial resources, based on both tangible and intangible criteria. The overall process is supported by a software platform developed in the scope of the EnPROVE project. The platform includes building audit, energy consumption prediction, and decision support. The decision support follows a benefits, opportunities, costs, and risks (BOCR) analysis based on the analytic hierarchy process (AHP). The proposed methodology and platform were tested and validated in a real business case, also within the scope of the project, demonstrating the expected benefits of alternative retrofit solutions focusing on lighting and thermal comfort.UNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasRUNNeves-Silva, RuiCamarinha-Matos, Luis M.2022-11-30T22:12:45Z2022-09-262022-09-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article18application/pdfhttp://hdl.handle.net/10362/145918eng2071-1050PURE: 47910110https://doi.org/10.3390/su141912216info: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:RCAAP2024-05-22T18:07:04Zoai:run.unl.pt:10362/145918Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:07:04Repositório 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 Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
title Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
spellingShingle Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
Neves-Silva, Rui
buildings industry
decision-support systems
energy efficiency
human-factor
simulation
Computer Science (miscellaneous)
Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Building and Construction
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Hardware and Architecture
Computer Networks and Communications
Management, Monitoring, Policy and Law
SDG 7 - Affordable and Clean Energy
title_short Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
title_full Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
title_fullStr Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
title_full_unstemmed Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
title_sort Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
author Neves-Silva, Rui
author_facet Neves-Silva, Rui
Camarinha-Matos, Luis M.
author_role author
author2 Camarinha-Matos, Luis M.
author2_role author
dc.contributor.none.fl_str_mv UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
CTS - Centro de Tecnologia e Sistemas
RUN
dc.contributor.author.fl_str_mv Neves-Silva, Rui
Camarinha-Matos, Luis M.
dc.subject.por.fl_str_mv buildings industry
decision-support systems
energy efficiency
human-factor
simulation
Computer Science (miscellaneous)
Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Building and Construction
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Hardware and Architecture
Computer Networks and Communications
Management, Monitoring, Policy and Law
SDG 7 - Affordable and Clean Energy
topic buildings industry
decision-support systems
energy efficiency
human-factor
simulation
Computer Science (miscellaneous)
Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Building and Construction
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Hardware and Architecture
Computer Networks and Communications
Management, Monitoring, Policy and Law
SDG 7 - Affordable and Clean Energy
description Publisher Copyright: © 2022 by the authors.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-30T22:12:45Z
2022-09-26
2022-09-26T00:00:00Z
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/10362/145918
url http://hdl.handle.net/10362/145918
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2071-1050
PURE: 47910110
https://doi.org/10.3390/su141912216
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 18
application/pdf
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 mluisa.alvim@gmail.com
_version_ 1817545901110984704

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