@article {30313,
	title = {Performance Evaluation of an Agent-based Occupancy Simulation Model},
	journal = {Building and Environment},
	volume = {115},
	year = {2017},
	month = {04/2017},
	abstract = {<p>Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.</p>},
	keywords = {model performance evaluation, occupancy pattern, Occupancy simulation, occupant behavior, occupant presence and movement, verification},
	doi = {10.1016/j.buildenv.2017.01.015},
	author = {Xuan Luo and Khee Poh Lam and Yixing Chen and Tianzhen Hong}
}
