Air Conditioning Consumption Optimization Based on CO2 Concentration Level
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2019 |
| Outros Autores: | , , |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/10400.22/18482 |
Resumo: | Nowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios. |
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Air Conditioning Consumption Optimization Based on CO2 Concentration LevelOptimizationPSOBuildingsCO2Nowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios.IEEEREPOSITÓRIO P.PORTOKhorram Ghahfarrokhi, MahsaZheiry, ModarFaria, PedroVale, Zita2021-09-22T14:28:04Z20192019-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.22/18482eng978-1-7281-3192-410.1109/ISAP48318.2019.9065967info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-02T03:02:12Zoai:recipp.ipp.pt:10400.22/18482Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:35:55.029456Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| title |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| spellingShingle |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level Khorram Ghahfarrokhi, Mahsa Optimization PSO Buildings CO2 |
| title_short |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| title_full |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| title_fullStr |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| title_full_unstemmed |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| title_sort |
Air Conditioning Consumption Optimization Based on CO2 Concentration Level |
| author |
Khorram Ghahfarrokhi, Mahsa |
| author_facet |
Khorram Ghahfarrokhi, Mahsa Zheiry, Modar Faria, Pedro Vale, Zita |
| author_role |
author |
| author2 |
Zheiry, Modar Faria, Pedro Vale, Zita |
| author2_role |
author author author |
| dc.contributor.none.fl_str_mv |
REPOSITÓRIO P.PORTO |
| dc.contributor.author.fl_str_mv |
Khorram Ghahfarrokhi, Mahsa Zheiry, Modar Faria, Pedro Vale, Zita |
| dc.subject.por.fl_str_mv |
Optimization PSO Buildings CO2 |
| topic |
Optimization PSO Buildings CO2 |
| description |
Nowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios. |
| publishDate |
2019 |
| dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z 2021-09-22T14:28:04Z |
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conference object |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/18482 |
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http://hdl.handle.net/10400.22/18482 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
978-1-7281-3192-4 10.1109/ISAP48318.2019.9065967 |
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info:eu-repo/semantics/openAccess |
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openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
IEEE |
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IEEE |
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reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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