Natural Ventilation for Passive Cooling by Means of Optimized Control Logics. (2017)
- Record Type:
- Journal Article
- Title:
- Natural Ventilation for Passive Cooling by Means of Optimized Control Logics. (2017)
- Main Title:
- Natural Ventilation for Passive Cooling by Means of Optimized Control Logics
- Authors:
- Rinaldi, Alessandro
Roccotelli, Michele
Mangini, Agostino Marcello
Fanti, Maria Pia
Iannone, Francesco - Abstract:
- Abstract: Natural ventilation is one of the most efficient solutions to improve thermal comfort in buildings, particularly for passive and hybrid cooling. This paper analyses the potential of building automation systems for ventilative cooling in residential buildings. In relation to internal and external temperature, an optimized control strategy of window opening is developed to ensure adequate levels of indoor thermal comfort, reducing energy consumption for cooling. In particular, the control of ventilation is calibrated by an optimized variable set-point and a Particle Swarm Optimization (PSO) method is adopted with objective function that minimizes the thermal discomfort hours. The PSO algorithm is implemented in MATLAB and integrated with TRNSYS energy simulation software. A case study focusing on an existing Italian typical building of the'60s, situated in the Mediterranean climatic context is presented. Thermal comfort analysis, according to the adaptive thermal comfort theory (EN 15251-2007), shows that the optimized control logics for natural ventilation determines a significant reduction of overheating discomfort in reference to the case with ventilation only for indoor air quality at fixed hours. Combining the passive cooling system with an active cooling, there are also reductions in energy consumptions for cooling. The results show how the proposed optimized control logics increase the potentialities of natural ventilation strategies to the improvement ofAbstract: Natural ventilation is one of the most efficient solutions to improve thermal comfort in buildings, particularly for passive and hybrid cooling. This paper analyses the potential of building automation systems for ventilative cooling in residential buildings. In relation to internal and external temperature, an optimized control strategy of window opening is developed to ensure adequate levels of indoor thermal comfort, reducing energy consumption for cooling. In particular, the control of ventilation is calibrated by an optimized variable set-point and a Particle Swarm Optimization (PSO) method is adopted with objective function that minimizes the thermal discomfort hours. The PSO algorithm is implemented in MATLAB and integrated with TRNSYS energy simulation software. A case study focusing on an existing Italian typical building of the'60s, situated in the Mediterranean climatic context is presented. Thermal comfort analysis, according to the adaptive thermal comfort theory (EN 15251-2007), shows that the optimized control logics for natural ventilation determines a significant reduction of overheating discomfort in reference to the case with ventilation only for indoor air quality at fixed hours. Combining the passive cooling system with an active cooling, there are also reductions in energy consumptions for cooling. The results show how the proposed optimized control logics increase the potentialities of natural ventilation strategies to the improvement of energy and thermal performance of buildings, integrating or replacing the conventional efficiency strategies. … (more)
- Is Part Of:
- Procedia engineering. Volume 180(2017)
- Journal:
- Procedia engineering
- Issue:
- Volume 180(2017)
- Issue Display:
- Volume 180, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 180
- Issue:
- 2017
- Issue Sort Value:
- 2017-0180-2017-0000
- Page Start:
- 841
- Page End:
- 850
- Publication Date:
- 2017
- Subjects:
- Natural ventilation -- Passive cooling -- Building automation -- Particle Swarm Optimization
Engineering -- Congresses
Engineering -- Periodicals
Engineering
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620.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/18777058 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.proeng.2017.04.245 ↗
- Languages:
- English
- ISSNs:
- 1877-7058
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14143.xml