Buildings.Occupants: a Modelica package for modelling occupant behaviour in buildings

Abstract

Energy-related occupant behavior is crucial to design and operation of energy and control systems in buildings. Occupant behaviors are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on cosimulation approaches or customized source code changes to building simulation programs. This paper presents Buildings.Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviors of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviors. The major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviors in buildings, and to develop an open-source Occupants package in the Modelica language.

Revisiting individual and group differences in thermal comfort based on ASHRAE database

“…The thermal comfort index of special interest in this study is neutral temperature and thermal sensitivity. We selected these two index because they are important in determining the HVAC temperature set-point (T neutral ) as well as the comfort range (T neutral ± k * thermalSensitivity ) 6 . It is worthy to point out that the thermal sensitivity defined in this study is the reciprocal of the Griffiths Constant.…”

“…However, field studies showed that occupants are not always satisfied with their indoor thermal environment [4], [5]. A major reason behind this problem is people respond differently to the same built environment [6] and have diversified thermal comfort preferences given the same ambient thermal environment [7], which could not be satisfied by a 'one-fits-all' centralized HVAC system without personal adaptation.…”

Linking human-building interactions in shared offices with personality traits

“…A well-designed HBI system encourages occupants to control the built environment to reduce energy use while enhancing their comfort [10], [11], productivity [12], and health [13]. Due to their importance in modern buildings, HBIs have become a popular topic [14], 3 new models have been introduced to simulate HBIs [15], and new tools have been developed [16].…”

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

“…For instance, using U.S. Department of Energy (DOE) reference models, the National Renewable Energy Laboratory (NREL) generated and open sourced hourly load profile data for 16 commercial building types on OpenEI. 2 However, the assumptions proposed by the modelers or in the reference building model may not necessarily reflect the reality of actual buildings [19], resulting in a gap in the load profiles between the white-box simulation and the real building [20].…”