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The analysis of factors affecting energy consumption of duplex residences in College Station, Texas.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The analysis of factors affecting energy consumption of duplex residences in College Station, Texas.
作者:	Kim, Suk Bong.
面頁冊數:	136 p.
附註:	Chair: Paul K. Woods.
附註:	Source: Dissertation Abstracts International, Volume: 59-04, Section: A, page: 0982.
Contained By:	Dissertation Abstracts International59-04A.
標題:	Architecture.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9830942
ISBN:	059183846X

The analysis of factors affecting energy consumption of duplex residences in College Station, Texas.
Kim, Suk Bong.

The analysis of factors affecting energy consumption of duplex residences in College Station, Texas.[electronic resource] - 136 p.

Chair: Paul K. Woods.

Thesis (Ph.D.)--Texas A&M University, 1998.

Some significant differences were found between the models which contained the weather-related factors and the models which did not contain the weather-related factors. This study demonstrated that weather-related factors were a very important factor in the analysis of energy consumption.

ISBN: 059183846XSubjects--Topical Terms:

208437
Architecture.

The analysis of factors affecting energy consumption of duplex residences in College Station, Texas.
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520 # $a Some significant differences were found between the models which contained the weather-related factors and the models which did not contain the weather-related factors. This study demonstrated that weather-related factors were a very important factor in the analysis of energy consumption.
520 # $a The overall purpose of this research was to characterize the variability of energy consumption due to a series of construction, occupant, and weather-related effects in duplex residences in College Station, Texas. Spline regression was used to estimate cooling efficiency, heating efficiency, base load, modified cooling balance temperature, and modified heating balance temperature for monthly billed kWh and average daily outside temperature. These estimates were used to predict normalized annual consumption. Best subsets regression and multiple regression were used to explore the relationship between energy consumption and construction, occupant, and weather-related factors. Normalized annual consumption, actual energy consumption, cooling efficiency, heating efficiency, and base load were used as dependent variables. Construction-related factors included market value, floor area, perimeter, length of common wall, year built, wall materials, roof reflectivity, shading factor, orientation perpendicular to the common wall, and number of bedrooms. There were seven occupant-related factors: winter thermostat-set temperature, summer thermostat-set temperature, programmable thermostat setting, adjusted thermostat setting, number of occupants, student or not, and monthly rent. Weather-related factors included cooling efficiency, heating efficiency, base load, modified cooling balance temperature, and modified heating balance temperature.
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