The effect of spatial and temporal randomness of stochastically generated occupancy schedules on the energy performance of a multiresidential building

被引:29
作者
Carlucci, Salvatore [1 ]
Lobaccaro, Gabriele [2 ]
Li, Yong [3 ]
Lucchino, Elena Catto [1 ]
Ramaci, Roberta [2 ]
机构
[1] NTNU Norwegian Univ Sci & Technol, Dept Civil & Transport Engn, Trondheim, Norway
[2] NTNU Norwegian Univ Sci & Technol, Dept Architectural Design Hist & Technol, Trondheim, Norway
[3] Shanghai Jiao Tong Univ, Inst Refrigerat & Cryogen, Shanghai, Peoples R China
关键词
Mathematical optimization; Multiresidential building; Occupancy models; Quality assurance; Spatial randomness; Temporal randomness; Shanghai; MULTIOBJECTIVE OPTIMIZATION; CO2; EMISSIONS; CONSUMPTION; URBANIZATION; PREDICTION; SIMULATION; BEHAVIOR;
D O I
10.1016/j.enbuild.2016.05.023
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Building performance simulation is frequently used to support building design, renovation, and operation. However, modelers are traditionally concerned with accurately describing technical input data, and have only limjted interest in investigating the influence of occupant behavior on buildings' energy performance. To fill this gap, this article examines the effects of stochastically generated occupancy schedules on the energy performance of a multiresidential high-rise building located in Shanghai, China. The building's energy performance is analyzed under two design proposals: a law-compliant proposal developed by the designers, and a second proposal conceived through an automatized optimization process. A statistical analysis quantifies the energy implications of adopting different degrees of randomness when creating occupancy and occupancy-dependent schedules. Simulation outcomes show that temporal and spatial randomness of occupancy and occupancy dependent schedules have a statistically significant influence on the building's energy performance, with an estimated uncertainty of up to 10%. At least in Shanghai, occupant behavior affects cooling more than heating, and its influence on the energy performance is stronger in high-performance buildings than in poorly insulated ones. Finally, accurate modeling of high-performance buildings would require a detailed and precise description of occupancy and occupant-dependent input variables even if this increases the modeling effort and costs. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:279 / 300
页数:22
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