دانلود مقاله ISI انگلیسی شماره 145642
ترجمه فارسی عنوان مقاله

برآورد پتانسیل انرژی خورشیدی در سقف های شیبدار

عنوان انگلیسی
Estimating solar energy potentials on pitched roofs
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
145642 2017 30 صفحه PDF
منبع

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

Journal : Energy and Buildings, Volume 139, 15 March 2017, Pages 101-107

ترجمه کلمات کلیدی
سقف ساختمان، شبیه سازی ساختمان، مدل سازی، برنامه نویسی، ارزیابی انرژی خورشیدی،
کلمات کلیدی انگلیسی
Building roofs; Building simulation; Modelling; Programming; Solar energy assessment;
پیش نمایش مقاله
پیش نمایش مقاله  برآورد پتانسیل انرژی خورشیدی در سقف های شیبدار

چکیده انگلیسی

Pitched-roof buildings make up a considerable proportion of architectural roof styles. Precise estimation of solar energy potential on pitched roofs is thus crucial to the sustainable development and renewable energy consumption of human habitats. Conventional solar radiation measurements usually adopt Light Detection and Ranging (LiDAR) data, which can only be extracted from existing buildings. There has been relatively little research assessing solar radiation on pitched roofs. This paper develops a pixel-based approach to estimation of solar energy potentials over pitched roofs based on the pretext of architectural design drawings. A typical Australian house with nine roofs is then chosen for implementation through a case study. The solar radiation on a certain cell of a shadow map is mathematically formulated for each pixel unit. Its yields over a certain time period are calculated by considering multiple instantaneous solar irradiances and visually presented through image processing. The resulting solar radiation maps, especially a coloured 3D map, reveal the roofs’ radiation distribution including effects from objects on the roofs such as chimneys. Radiation contour lines are mapped to obtain installation ranges for solar devices. This study will benefit commercial energy investors, residents and urban planners in the efficient use of renewable energy sources through accurate prediction of solar radiation potential and identification of areas receiving high radiation over sloping roofs.