Energy Use Intensity Estimation Method Based on Façade Features

Abstract

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.