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Air Conditioning Consumption Optimization Based on CO2 Concentration Level

2019Conference object Open access
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dc.contributor.authorKhorram Ghahfarrokhi, Mahsa
dc.contributor.authorZheiry, Modar
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-09-22T14:28:04Z
dc.date.available2021-09-22T14:28:04Z
dc.date.issued2019
dc.description.abstractNowadays, 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.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: COLORS Project, CEECIND/02887/2017, and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and National Funds through FCT.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ISAP48318.2019.9065967pt_PT
dc.identifier.isbn978-1-7281-3192-4
dc.identifier.urihttp://hdl.handle.net/10400.22/18482
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationCEECIND/02887/2017pt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9065967pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/pt_PT
dc.subjectOptimizationpt_PT
dc.subjectPSOpt_PT
dc.subjectBuildingspt_PT
dc.subjectCO2pt_PT
dc.titleAir Conditioning Consumption Optimization Based on CO2 Concentration Levelpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F00760%2F2019/PT
oaire.citation.conferencePlaceNew Delhi, Indiapt_PT
oaire.citation.endPage5pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameKhorram Ghahfarrokhi
person.familyNameFaria
person.familyNameVale
person.givenNameMahsa
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-id9719-75D7-B785
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-0581-2898
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id57201796142
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
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