2012
DOI: 10.3130/jaabe.11.383
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A Development of Energy Load Prediction Equations for Multi-Residential Buildings in Korea

Abstract: The study intends to develop energy load prediction equations which can be easily used to estimate the energy consumption of multi-residential buildings in the central climatic zone in Korea during the early design stage. Based on an intensive literature search, energy strategies and performance levels which affect heating and cooling energy consumption were established for a reference baseline building. To analyze the sensitivity of each energy strategy to overall performance, the table of Orthogonal Array wa… Show more

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Cited by 11 publications
(4 citation statements)
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“…Hubacek et al [19] examined the contribution to CO 2 emissions (I) of population growth (P), affluence (A) (representing different lifestyles and consumption patterns) and CO 2 intensity (T) representing technology. Kang et al [20] developed energy load prediction equations which can be easily used to estimate the energy consumption of multi-residential buildings in Korea by using Orthogonal Array to carry out simulation and investigated the relative importance of each energy factor with ANOVA. Yoo et al [21] identified the changes in occupants' lifestyles using national statistics survey data, and then estimations were made by connecting each occupant activities to the corresponding residential appliances.…”
Section: Study Of Literaturementioning
confidence: 99%
“…Hubacek et al [19] examined the contribution to CO 2 emissions (I) of population growth (P), affluence (A) (representing different lifestyles and consumption patterns) and CO 2 intensity (T) representing technology. Kang et al [20] developed energy load prediction equations which can be easily used to estimate the energy consumption of multi-residential buildings in Korea by using Orthogonal Array to carry out simulation and investigated the relative importance of each energy factor with ANOVA. Yoo et al [21] identified the changes in occupants' lifestyles using national statistics survey data, and then estimations were made by connecting each occupant activities to the corresponding residential appliances.…”
Section: Study Of Literaturementioning
confidence: 99%
“…Meanwhile, other previous studies were conducted to accurately predict the building energy consumption using the simulation tool and the data-mining technique [30][31][32][33][34][35][36]. Li et al [30] and Foucquier et al [31] have reviewed the state of the art in building modeling and energy performance prediction and have analyzed in terms of three categories (i.e., black box method, gray box method, and white box method).…”
Section: Research Background and Objectivementioning
confidence: 99%
“…Variations in the design and construction of Korean residential buildings are very small and limited relative to other building types (Kang & Rhee, 2012). In Korea, the required size and number of elevators for a given building are defined by the National Building Codes.…”
Section: Building Datamentioning
confidence: 99%