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From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency.

Authors :
Jia, Mengda
Srinivasan, Ravi S.
Raheem, Adeeba A.
Source :
Renewable & Sustainable Energy Reviews. Feb2017 Part 1, Vol. 68, p525-540. 16p.
Publication Year :
2017

Abstract

Energy consumption and indoor environment of buildings are proved to be largely influenced by the presence and behaviors of occupants. The uncertainty caused by occupant behaviors accounts for a significant discrepancy between the predicted and actual energy usage. In a real world, building system operations and control will be directly affected by occupant behavior, which may lead to over thirty percent waste against building's designed performance. Therefore, the capability to seamlessly integrate occupant behavior in energy simulation tools and building management systems in the future is clearly important to optimize building energy use while maintaining the same level of services. However, research has not reached the phase that occupant behaviors could be effectively modeled. Thus, the traditional schedule based approach is not adequate to satisfy the needs of building efficiency. In this paper, a thorough survey of occupant behavior modeling and simulation state-of-the-art technologies and methodologies for building energy efficiency is conducted. The paper first identifies and discusses the significance and application scale of building occupant behavior model. Based on the information collected, some recent data acquisition technologies for behavior-related research and occupant behavior modeling approaches are summarized. The advantages and limitations of these modeling methods are compared and analyzed, as well as appropriate recommendations are made for the future research. The paper finally outlines the findings and potential development areas in the field of occupant behavior modeling for energy efficient buildings. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13640321
Volume :
68
Database :
Academic Search Index
Journal :
Renewable & Sustainable Energy Reviews
Publication Type :
Academic Journal
Accession number :
119781258
Full Text :
https://doi.org/10.1016/j.rser.2016.10.011