An agent-based stochastic Occupancy Simulator

Abstract

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with Reinhart's LIGHTSWITCH-2002 model, (2) the random moving events (e.g., from one office to another) simulated with Wang's homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building.The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes 1 enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.

Context-specific urban occupancy modeling using location-based services data

“…Namely, Chang's model [27] to simulate the occupancy state of a space, Page's model [28] to simulate the number of occupants in a space, and Wang's model [29] to generate the spatial location of each occupant and the space-level occupancy for the whole building. As part of IEA EBC Annex 66 and Annex 79 data-based models and agent-based models for building occupancy have been developed [30,31,32,33,34,35,36]. In [31], data-mining methods were used to derive office occupancy schedules from appliance power consumption measurements.…”

“…In [35], machine learning techniques were used for daily occupancy patterns recognition for improving the energy efficiency of an office building. An agent-based model for office buildings has been developed by [36]. It is depending on expert user inputs, such as, e.g., the typical arrival times of each occupant, the number of planned meetings per day, and the probability distribution of meeting durations.…”

A review on occupant behavior in urban building energy models

“…The aggregated presence and actions of all persons in a certain space yield the same model output as a space-based approach. Examples of person-based approaches include the agent-based stochastic occupancy simulator for office buildings by Chen et al [65,66].…”

Building simulation: Ten challenges

“…Modeling and simulation efforts that span multiple technical domains usually require the use of several different simulation tools, which may cover building energy flows (e.g., EnergyPlus), distributed energy resources (e.g., DER-CAM), CFD (e.g., FLUENT), grid conditions (e.g., the Integrated Grid Modeling System IGMS), and human behavior (e.g., agent-based modeling tool AnyLogic, obXML and obFMU (Hong et al 2015b(Hong et al , 2015c, Occupancy Simulator (Chen et al 2017b)). Various approaches have been developed (Trcka et al 2009;Wetter 2011) to couple cross-domain tools through co-simulation.…”