Prediction Equations for Energy Consumption Through Surveys on Energy Consumption in Apartment Buildingsopen access
- Authors
- Ju, Jung Hoon; Park, Seol Hui; Park, Sung Jo; Park, Jin Chul; Rhee, Eon Ku
- Issue Date
- Sep-2014
- Publisher
- ARCHITECTURAL INST JAPAN
- Keywords
- apartment buildings; energy consumption survey; shading analysis simulation; prediction equation for energy consumption
- Citation
- JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING, v.13, no.3, pp 657 - 664
- Pages
- 8
- Journal Title
- JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING
- Volume
- 13
- Number
- 3
- Start Page
- 657
- End Page
- 664
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/11887
- DOI
- 10.3130/jaabe.13.657
- ISSN
- 1346-7581
1347-2852
- Abstract
- This study presents energy consumption prediction equations developed by conducting multiple regression analyses of data collected in surveys of actual states of energy consumption in apartment buildings in their operational stage. Surveys of actual states of average energy consumption per unit show that 1) the largest component of energy consumption is room heating, followed by electricity, hot water supply, and gas, in that order; 2) energy consumption increases with household area; 3) among exposures, energy consumption is highest in households facing east or northeast and lowest in those facing south or southwest; 4) among height types, energy consumption is highest in super-high-rise apartment buildings (50 stories or higher), followed by semi-super-high-rises, high-rises, and medium-high-rises, in that order; and 5) among plan types, tower-type apartment buildings use approximately 17% - 20% more energy than flat types. The goodness-of-fit criterion stated in the 2009 ASHRAE Fundamentals Handbook (SI) Edition is shown to be satisfied for the equations presented in this paper for the prediction of energy consumption of apartment buildings in their operational stage. These equations were developed through multiple regression analysis using the areas and heat transmission coefficients of structures as independent variables and using energy consumption as the dependent variable.
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