Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
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Domestic Hot Water Load Prediction in Residential Communities using the Structured Probabilistic Statistical Models

구조화된 확률적 통계 모델 개발을 통한 주거 커뮤니티 급탕 수요 예측

  • Kim, Chulho (Department of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Byun, Jiwook (Department of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Go, Jaehyun (Department of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Heo, Yeonsook (Department of Civil, Environmental and Architectural Engineering, Korea University)
  • 김철호 (고려대 건축사회환경공학과) ;
  • 변지욱 (고려대 건축사회환경공학과) ;
  • 고재현 (고려대 건축사회환경공학과) ;
  • 허연숙 (고려대 건축사회환경공학과)
  • Received : 2021.12.22
  • Accepted : 2022.03.17
  • Published : 2022.03.30
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Abstract

This study developed structured probabilistic statistical models to systematically reflect individual variations in the domestic hot water load factoring household characteristics and temporal variations in the hourly pattern of consumption. The hourly domestic hot water data of 15 households derived from the Korea Energy Agency's public data were used. Models 1 and 2 were based on bilinear regression models to predict the daily average domestic hot water load based on the household characteristics and daily variations. Model 3 was based on the multivariate normal distribution to generate the average hourly domestic hot water load profile which varied per household. Model 4 used the beta distribution probability density function to randomly generate hourly variations from the average load profiles reflecting temporal variation. As a result of applying these four models, individual and temporal variations were reflected in the whole year hourly load prediction. The resulting probabilistic domestic hot water loads were compared with those determined using the deterministic method of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), ECO2 criteria and the single multivariate distribution model derived during the entire set of hourly load data across the 15 households. This comparison reflected that the structured probabilistic models predicted individual and temporal variations with sufficient accuracy.

Keywords

Acknowledgement

본 연구는 국토교통부 / 국토교통과학기술진흥원의 지원으로 수행되었음 (과제번호 KAIA22HSCT-C157909-03).

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