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ENERGY USE INTENSITY ESTIMATION METHOD BASED ON BUILDING FAÇADE FEATURES BY USING REGRESSION MODELS
By
CHAO YANG
A Thesis report presented to the FACULTY OF SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In partial fulfillment of the Requirements of the degree MASTER OF BUILDING SCIENCE
MAY 2015
Copyright 2015 Chao Yang
Object Description
| Title | Energy use intensity estimation method based on building façade features by using regression models |
| Author | Yang, Chao |
| Author email | chaoyang@usc.edu;chaoyang@usc.edu |
| Degree | Master of Building Science |
| Document type | Thesis |
| Degree program | Building Science |
| School | School of Architecture |
| Date defended/completed | 2015-03-23 |
| Date submitted | 2015-04-23 |
| Date approved | 2015-04-24 |
| Restricted until | 2017-04-23 |
| Date published | 2017-04-23 |
| Advisor (committee chair) | Choi, Joon-Ho |
| Advisor (committee member) |
Noble, Douglas Schiler, Marc |
| Abstract | The commercial and residential building sector accounts for about 40% of carbon dioxide (CO₂) emissions in the United States per year, more than any other sector (Eddy and Marton 2012). The most significant factor contributing to CO₂ emissions from buildings is their use of electricity. Commercial and residential buildings are tremendous users of electricity (Department of Energy 2011), accounting for more than 73% of electricity use in the U.S. ❧ Energy use data from the Commercial Building Energy Consumption Survey (CBECS) is an average value based on the range of Heating Degree Days (HDD) and Cooling Degree Days (CDD), which can’t show the specific condition of each building category within one area. In addition, the average value is too general to evaluate if a specific building case is energy efficient or not. On the other hand, it is very time consuming to develop a simulation model in software, which also needs very detailed information about the building itself. The accuracy depends on how much specific information of envelop thermal conditions, mechanical system performance, occupancy level and schedule, etc. ❧ Among 3 main factors to influence building energy performance, building façade features are more easily obtained as opposed to building mechanical systems and schedule information. By using façade features, certain key attributes could be input to generate a customized baseline model and to estimate building energy use intensity (EUI). ❧ A simple regression model can be used to calculate the EUI baseline instead of complicated simulation tools, and the results are accurate and reasonable at an acceptable level. The calculated baseline can be used for setting a practical baseline for energy reduction target. Due to its simplicity and quick processing time, the research outcome would also be applicable to the real-time energy estimation of multiple buildings at an urban scale. ❧ This new method of linear regression analysis is developed to estimate building energy consumption just based on simple façade attributes and weather conditions. Building façade features, for example, including shading, window-to-wall ratio, orientation, surface-to-volume ratio, etc. are easy to obtain. It is meaningful to use a simple way to predict heating and cooling energy use instead of traditional energy performance simulation tool which is time and resource consuming. Based on collected building physical attribute data, statistical methods could be used to generate a customized baseline Energy Use Intensity (EUI) estimation model. The proposed idea will also adopt a simplified building energy performance prediction model as a function of architectural physical frames and their dynamic ambient environmental condition, such as monthly cooling/heating degree days. The main goal of this research is to develop a mathematical method to provide a customized baseline model for buildings, considering specific façade features and local climate condition. It will provide a direct estimation and prediction of project building energy performance to provide a reasonable baseline for designer, engineer and client. |
| Keyword | energy use intensity; facade; regression; baseline model |
| Language | English |
| Format (imt) | application/pdf |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Yang, Chao |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-YangChao-3393.pdf |
| Archival file | Volume2/etd-YangChao-3393.pdf |
Description
| Title | Page 1 |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 1 ENERGY USE INTENSITY ESTIMATION METHOD BASED ON BUILDING FAÇADE FEATURES BY USING REGRESSION MODELS By CHAO YANG A Thesis report presented to the FACULTY OF SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In partial fulfillment of the Requirements of the degree MASTER OF BUILDING SCIENCE MAY 2015 Copyright 2015 Chao Yang |
