کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5028990 | 1470646 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Natural Ventilation for Passive Cooling by Means of Optimized Control Logics
ترجمه فارسی عنوان
تهویه طبیعی برای خنک کننده منفی با استفاده از منطق کنترل بهینه شده
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کلمات کلیدی
تهویه طبیعی، خنک کننده منفعل، اتوماسیون اداری، بهینه سازی ذرات ذرات،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Engineering - Volume 180, 2017, Pages 841-850
Journal: Procedia Engineering - Volume 180, 2017, Pages 841-850
نویسندگان
Alessandro Rinaldi, Michele Roccotelli, Agostino Marcello Mangini, Maria Pia Fanti, Francesco Iannone,