کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
855668 1470708 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy Use Intensity Estimation Method Based on Façade Features
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی (عمومی)
پیش نمایش صفحه اول مقاله
Energy Use Intensity Estimation Method Based on Façade Features
چکیده انگلیسی

In the U.S., over 72% of the total generated power is consumed by commercial and residential buildings. Among a building's envelope, system, and control, which significantly influence the building's energy performance, façade is a major parametric element that accounts for 70% of its energy performance. Compared with the internal mechanical system and operation schedule, façade features information is relatively easy to obtain from the visual aspects of a building. By adopting several key façade attributes, a customized energy use intensity baseline model can be generated by considering building design features. Therefore, instead of using traditional and complicated simulation methods, a mathematical model can be established to estimate EUI baselines based on sufficient existing building practices data. In a national building performance survey, data such as CBECS and building energy usage are collected for a large database to provide performance guidance for new or renovation building projects. Unfortunately, averaged performance data are too aggregated and generic to identify specific conditions for each building category in a specific climate condition. In this research, a vision-based performance prediction model was developed to estimate building energy consumption based on simplified façade attribute information and weather conditions. Data about building façade features, including orientation, façade area, window-to-wall ratio, volume, surface-to-volume ratio, etc., were collected along with energy use public disclosure. A prediction model, based on this dataset, was established to estimate building energy use intensity as a function of façade features. This prediction approach will provide a more realistic EUI estimation tool for calculating an energy use baseline and will enable real-time energy usage monitoring and management of each target building.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Engineering - Volume 118, 2015, Pages 842-852