Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings.
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| Title: | Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings. |
|---|---|
| Authors: | Korkidis, Panagiotis1 (AUTHOR) p.korkidis@uniwa.gr, Dounis, Anastasios1 (AUTHOR) p.korkidis@uniwa.gr, Kofinas, Panagiotis1 (AUTHOR) |
| Source: | Energies (19961073). Aug2021, Vol. 14 Issue 16, p4971. 1p. |
| Subject Terms: | *Indoor air quality, *Evolutionary algorithms, *Thermal comfort, *Energy consumption, *Parameter estimation, *Computational intelligence |
| Abstract: | This paper focuses on the development of a multi agent control system (MACS), combined with a stochastic based approach for occupancy estimation. The control framework aims to maintain the comfort levels of a building in high levels and reduce the overall energy consumption. Three independent agents, each dedicated to the thermal comfort, the visual comfort, and the indoor air quality, are deployed. A stochastic model describing the CO2 concentration has been studied, focused on the occupancy estimation problem. A probabilistic approach, as well as an evolutionary algorithm, are used to provide insights on the stochastic model. Moreover, in order to induce uncertainty, parameters are treated in a fuzzy modelling framework and the results on the occupancy estimation are investigated. In the control framework, to cope with the continuous state-action space, the three agents utilise Fuzzy Q -learning. Simulation results highlight the precision of parameter and occupancy estimation, as well as the high capabilities of the control framework, when taking into account the occupancy state, as energy consumption is reduced by 55.9 % , while the overall comfort index is kept in high levels, with values close to one. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 152127291 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Korkidis%2C+Panagiotis%22">Korkidis, Panagiotis</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> p.korkidis@uniwa.gr</i><br /><searchLink fieldCode="AR" term="%22Dounis%2C+Anastasios%22">Dounis, Anastasios</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> p.korkidis@uniwa.gr</i><br /><searchLink fieldCode="AR" term="%22Kofinas%2C+Panagiotis%22">Kofinas, Panagiotis</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Aug2021, Vol. 14 Issue 16, p4971. 1p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Indoor+air+quality%22">Indoor air quality</searchLink><br />*<searchLink fieldCode="DE" term="%22Evolutionary+algorithms%22">Evolutionary algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Thermal+comfort%22">Thermal comfort</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br />*<searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br />*<searchLink fieldCode="DE" term="%22Computational+intelligence%22">Computational intelligence</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper focuses on the development of a multi agent control system (MACS), combined with a stochastic based approach for occupancy estimation. The control framework aims to maintain the comfort levels of a building in high levels and reduce the overall energy consumption. Three independent agents, each dedicated to the thermal comfort, the visual comfort, and the indoor air quality, are deployed. A stochastic model describing the CO2 concentration has been studied, focused on the occupancy estimation problem. A probabilistic approach, as well as an evolutionary algorithm, are used to provide insights on the stochastic model. Moreover, in order to induce uncertainty, parameters are treated in a fuzzy modelling framework and the results on the occupancy estimation are investigated. In the control framework, to cope with the continuous state-action space, the three agents utilise Fuzzy Q -learning. Simulation results highlight the precision of parameter and occupancy estimation, as well as the high capabilities of the control framework, when taking into account the occupancy state, as energy consumption is reduced by 55.9 % , while the overall comfort index is kept in high levels, with values close to one. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=152127291 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en14164971 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: 4971 Subjects: – SubjectFull: Indoor air quality Type: general – SubjectFull: Evolutionary algorithms Type: general – SubjectFull: Thermal comfort Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Computational intelligence Type: general Titles: – TitleFull: Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Korkidis, Panagiotis – PersonEntity: Name: NameFull: Dounis, Anastasios – PersonEntity: Name: NameFull: Kofinas, Panagiotis IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 08 Text: Aug2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 14 – Type: issue Value: 16 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
