Predictive models of energy consumption in multi-family housing in College Station, Texas /
Patterns of energy consumption in apartment buildings are different than those in single-family houses. Apartment buildings have different physical characteristics, and their inhabitants have different demographic attributes. This study develops models that predict energy usage in apartment building...
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| Format: | Thesis Book |
| Language: | English |
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[Place of publication not identified] :
[publisher not identified] ;
1999.
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| Subjects: | |
| Online Access: | http://proxy.library.tamu.edu/login?url=http://proquest.umi.com/pqdweb?did=730829691&sid=1&Fmt=2&clientId=2945&RQT=309&VName=PQD |
| Summary: | Patterns of energy consumption in apartment buildings are different than those in single-family houses. Apartment buildings have different physical characteristics, and their inhabitants have different demographic attributes. This study develops models that predict energy usage in apartment buildings in College Station. This is accomplished by analyzing and identifying the predictive variables that affect energy usage, studying the consumption patterns, and creating formulas based on combinations of these variables. According to the hypotheses and the specific research context, a cross-sectional design strategy is adopted. This choice implies analyses across variations within a sample of fourplex apartments in College Station. The data available for analysis include the monthly billing data along with the physical characteristics of the building, climate data for College Station, and occupant demographic characteristics. A simple random sampling procedure is adopted. The sample size of 176 apartments is drawn from the population in such a way that every possible sample has the same chance of being selected. Statistical methods used to interpret the data include univariate analysts (mean, standard deviation, range, and distribution of data), correlation analysis, regression analysis, and ANOVA (analyses of variance). The results show there are significant differences in cooling efficiency and actual energy consumption among different building types, but there are no significant differences in heating consumption. There are no significant differences in actual energy consumption between student and non-student groups or among ethnic groups. The findings indicate that there are significant differences in actual energy consumption among marital status groups and educational level groups. The multiple regression procedures show there is a significant relationship between normalized annual consumption and the combined variables of floor area, marital status, dead band, construction material, summer thermostat setting, heating slope, and base load, as well as a relationship between cooling slope and the combined variables of share wall, floor level, summer thermostat setting, external wall, and American household. In addition, there is a significant relationship between heating slope and the combined variables of winter thermostat setting, market value, student, and rent. The results also indicate there is a relationship between base load and the combined variables of floor area, market value, age of the building, marital status, student, and summer thermostat setting. |
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| Item Description: | Vita. "Major Subject: Architecture". |
| Physical Description: | xvi, 159 leaves : illustrations ; 28 cm. Issued also on microfiche from University Microfilm Inc. |
| Bibliography: | Includes bibliographical references (leaves 147-150). |