دانلود مقاله ISI انگلیسی شماره 64819
ترجمه فارسی عنوان مقاله

تاثیر پوشش گیاهی بر تعادل کل انرژی بام سبز و انرژی ساختمان مصرف

عنوان انگلیسی
Influence of plant coverage on the total green roof energy balance and building energy consumption
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
64819 2015 13 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy and Buildings, Volume 103, 15 September 2015, Pages 1–13

ترجمه کلمات کلیدی
شبیه سازی انرژی ساختمان ؛ بام سبز ؛ پوشش گیاهی؛ تعادل انرژی سطحی
کلمات کلیدی انگلیسی
Building energy simulation; Green roof; Plant coverage; Surface energy balance
پیش نمایش مقاله
پیش نمایش مقاله  تاثیر پوشش گیاهی بر تعادل کل انرژی بام سبز و انرژی ساختمان مصرف

چکیده انگلیسی

This study quantifies the influence of green roof plant coverage on the building energy consumption and the substrate energy balance components. The analysis started with the implementation of a green roof model that accounts for the effects of plant coverage into the U.S. Department of Energy (DOE) building energy simulation program, EnergyPlus. Using the DOE reference building models, thirty different cases were simulated considering different green roof plant coverage, building type, and building age for two different climates. The results indicated that the green roof substrate surface temperature decreases with increasing plant coverage. This temperature decrease is primarily due to the decrease in the amount of absorbed solar radiation on the substrate surface and also an increase in the substrate surface evaporation. For the base-case simulation, due to the plant shading effects, the total daily received radiation at the bare-soil surface is 32% (6.2 kWh m−2) higher than that at the fully-covered green roof substrate surface. Furthermore, the annual cooling (heating) load decreases (increases) with the rate of 13 (0.88) kWh m−2 of plant coverage area. The aim of this study is to show the importance of considering plant coverage in green roof simulations and building energy demand predictions.