کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4917359 | 1428379 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
FAST energy and daylight optimization of an office with fixed and movable shading devices
ترجمه فارسی عنوان
بهینه سازی سریع انرژی و روزآمد یک دفتر با دستگاه های سایه دار ثابت و متحرک
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کلمات کلیدی
نور روز بهینه سازی، سطح پاسخ، الگوریتم ژنتیک، انرژی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
This paper describes the Energy and Daylighting optimization of a fixed inclined panel which shades an office room with a south exposed window. The window features also user deployable internal Venetian blinds. Energy analysis takes into account the primary energy required for heating, cooling and artificial lights. Different numerical codes have been employed in order to perform the simulations required by the optimization process: Daysim estimates the artificial light consumption based on daylighting distribution, ESP-r computes heating and cooling loads and modeFRONTIER integrates the simulation codes in an automatic optimization loop. The performance of an algorithm specifically designed to deal with problems involving long simulation times (combining response surfaces and genetic algorithms) has been successfully evaluated; the algorithm has then been applied in the optimization loop. The optimized solutions are analysed in this paper, in particular three solutions have been selected: minimum primary energy consumption, minimum hours of blind deployed and an intermediate solution. The analysis compares the primary energy consumption and daylighting performance on the basis of the Useful Daylight Illuminance indicator and the time history of illuminance on predefined locations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Building and Environment - Volume 113, 15 February 2017, Pages 175-184
Journal: Building and Environment - Volume 113, 15 February 2017, Pages 175-184
نویسندگان
Marco Manzan, Alberto Clarich,