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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Energy and Buildingsarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Energy and Buildings
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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An occupancy-based model for building electricity consumption prediction: A case study of three campus buildings in Tianjin

Authors: Shuxue Han; Zhaoxia Wang; Neng Zhu; Qiaochu Wang; Yan Ding;

An occupancy-based model for building electricity consumption prediction: A case study of three campus buildings in Tianjin

Abstract

Abstract The accurate prediction of a building's electricity consumption can provide baselines for energy management and indicate the building's energy-saving potential. However, electricity utilization indicators based on the building area are no longer applicable because of the overall increase in the building area per person and occupant energy demand of buildings. To tackle this challenge, the building electricity consumption was split into ‘basic’ and ‘variable’ forms in this study and a two-part building electricity consumption prediction model based on human behavior was established. The basic electricity consumption is related to the building area, while the variable electricity consumption is related to the building occupancy. The probability function and Markov model were used to describe the electricity consumption caused by the randomness of occupancy in buildings. The model was validated using three campus buildings. Based on the comparison of the actual electricity bills of the campus buildings with the model prediction results, the model accuracy error is less than 5%. The results show that the building electricity consumption of a building has a growth limit when multiple people share a room, which is related to a person's initiative or ability to control the electricity use.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 10%