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Amina Irakoze(아미나 이라코제),Seok So-I(석소이),Kwanho Lee(이관호),Kee Han Kim(김기한) 대한건축학회 2022 대한건축학회 학술발표대회 논문집 Vol.42 No.2
An effective energy upgradation of existing building stock requires classification of buildings based on their thermal characteristics. The purpose of this study is to classify buildings with similar envelop thermal characteristics by applying k-means clustering analysis on building energy consumption data of different granularity (hourly, daily, and monthly energy). Heating energy consumption from 51 building models with varying wall, window, and roof thermal transmittance, window SHGC, and infiltration rate (ac/h) is used. The findings of this study indicate that building classifications obtained from hourly, daily, and monthly heating energy differ especially in the identification of buildings with high window thermal transmittance and infiltration rate.