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An Analysis of Energy Consumption Types Considering Life Patterns of Single-person Households
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1인 가구 거주자의 생활패턴이 고려된 에너지소요량 유형 분석

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Type
Academic journal
Author
Lee, Seunghui (세종대학교) Jung, Sungwon (세종대학교) Lim, Ki-Taek (부경대학교)
Journal
ARCHITECTURAL INSTITUTE OF KOREA JOURNAL OF THE ARCHITECTURAL INSTITUTE OF KOREA Planning & Design Vol.35 No.1(Wn.363) KCI Excellent Accredited Journal
Published
2019.1
Pages
37 - 46 (10page)

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An Analysis of Energy Consumption Types Considering Life Patterns of Single-person Households
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Research history (2)

2020

An Analysis and Prediction of Energy consumption in a building using life patterns of Single-Person Households
이승희 건축학과 2020.01 Thesis

2019

An Analysis of Energy Consumption Types Considering Life Patterns of Single-person Households
Lee ,  Seunghui ,  Jung JOURNAL OF THE ARCHITECTURAL INSTITUTE OF KOREA Planning & Design 2019.01 Academic journal
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Abstract· Keywords

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The energy of the building is influenced by the user"s activity due to the population, society, and economic characteristics of the building user. In order to obtain accurate energy information, the difference in the amount of energy consumption by the activities and characteristics of building users should be identified. The purpose of the study is to identify the difference in the amount of energy consumption by the user"s activities in the same building, and to analyse the relationship between user"s activities and demographic, social and economic characteristics. For research, energy simulation is performed based on actual user activity schedule. The results of the simulation were clustered by using K-Means clustering, a machine learning technique. As a result, four types of users were derived based on the amount of energy consumption. The more energy used in a cluster, the lower the user"s income level and older. The longer a user"s indoor activity times, the higher the energy use, and these activities relate to the user"s characteristics. There is more than twice the difference between the group that uses the least energy consumption and the group that uses the most energy consumption.
#건축물에너지효율등급 #1인 가구 #에너지 플러스 #머신러닝 #유저 클러스터링 #Building energy efficiency rating #Single person household #Energy Plus #Machine Learning #User Clustering

Contents

Abstract
1. 서론
2. 이론고찰
3. 에너지 시뮬레이션
4. 클러스터링
5. 결론
REFERENCES

References (19)

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An, K. H., & Kim, I. S. (2013). Based on the Building Users, Fundamental Research in the Development of Energy Demand Forecasting and Evaluation Methods, Journal of The Architectural Institute of KOREA Planning & Design, 29(3), 41-48 google schola Lee, E., Chung, K., & Kim Y. (2016). Evaluation of building energy efficiency according to the air-conditioner installation in collective housings by using ECO2 software, The Society of Air-Conditioning And Refrigerating Engineers of Korea, 82-85 google schola Turner, C., & Frankel, M. (2008). Energy performance of LEEDⓡ for new construction buildings. New Buildings Institute, US Green Building Council. google schola Lee, M. J., & Kim, J. U. (2015). A Study of Domestic and Foreign System and Evaluate Tools Relative to Building Energy Performance Analysis and Improvement Plan for Zero Energy Building Design, Journal of The Architectural Institute of KOREA Planning & Design, 31(4), 45-52 google schola Bourgeois D., Reinhart C., & Iain A. (2006). Adding advanced behavioural models in whole building energy simulation: a study on the total energy impact of manual and automated lighting control, Energy and Buildings, 38, 814-82. google schola

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