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dc.contributor.author
Schierloh, R.M.
dc.contributor.author
Bragagnolo, Sergio Nicolás
dc.contributor.author
Vega, Jorge Ruben
dc.contributor.author
Vaschetti, Jorge Carlos
dc.date.available
2024-03-07T11:52:49Z
dc.date.issued
2023-09
dc.identifier.citation
Schierloh, R.M.; Bragagnolo, Sergio Nicolás; Vega, Jorge Ruben; Vaschetti, Jorge Carlos; Real-Time predictive management of a multi-unit HVAC system based on heuristic optimization: A health center case study; Elsevier Science SA; Energy and Buildings; 295; 113315; 9-2023; 1-12
dc.identifier.issn
0378-7788
dc.identifier.uri
http://hdl.handle.net/11336/229638
dc.description.abstract
Heating, ventilation, and air conditioning (HVAC) systems have a high energy consumption, so their control and management strategies have an important role today to improve the efficiency and reduce cost of power systems. This work proposes an optimal real-time management scheme for multi-units HVAC systems based on a predictive control that seeks to maximize thermal comfort while minimizing electric energy cost, applicable to multi-zone buildings and useful for low-cost implementations. The optimization problem is formulated to be solved with a heuristic approach using simple variable prediction models of outdoor temperature, room occupancy and load demand, developed using level reconciliation with average profiles. The scheme is applied to the study case of a radiotherapy and medical imaging center HVAC system, in Argentina. The performance of the strategy is evaluated using variable prediction models (real forecasting), perfect prediction (ideal forecasting), and different prediction horizons (of 1, 2 and 3 h) for the predictive controller. Additionally, the strategy is compared against an improved on–off control by temperature bands with and without peak clipping, showing that the proposed strategy improves the thermal comfort (up to 47 %) and achieves a low electrical cost, particularly compared to the strategy without peak clipping (23 % decrease).
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science SA
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
DEMAND RESPONSE
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GENETIC ALGORITHM
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HVAC MANAGEMENT
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MODEL PREDICTIVE CONTROL
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REAL-TIME OPTIMIZATION
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THERMAL MODEL
dc.subject.classification
Control Automático y Robótica
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Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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INGENIERÍAS Y TECNOLOGÍAS
dc.title
Real-Time predictive management of a multi-unit HVAC system based on heuristic optimization: A health center case study
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-03-04T12:33:12Z
dc.journal.volume
295
dc.journal.number
113315
dc.journal.pagination
1-12
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Schierloh, R.M.. Universidad Tecnológica Nacional. Facultad Regional Paraná; Argentina
dc.description.fil
Fil: Bragagnolo, Sergio Nicolás. Universidad Tecnológica Nacional. Facultad Regional Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Vega, Jorge Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina. Universidad Tecnológica Nacional. Facultad Regional Santa Fe; Argentina
dc.description.fil
Fil: Vaschetti, Jorge Carlos. Universidad Tecnológica Nacional. Facultad Regional Córdoba; Argentina
dc.journal.title
Energy and Buildings
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.enbuild.2023.113315
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378778823005455
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