Simulating multiple occupant behaviors in buildings: An agent-based modeling approach

Abstract

A new simulation methodology using agent-based modeling is presented to simulate multiple, occupant behaviors in a commercial building. The purpose of the agent-based modeling is to mimic a real-world occupant: an autonomous agent that interacts with both its environment and other agents, and makes behavior decisions based on the level of its thermal comfort. First, individual agent behaviors are simulated; second, the results are aggregated to explain the behavioral phenomena of the building as a whole. Using simulation coupling, the behavior impact on the thermal conditions and, energy use can be scrutinized. A simple simulation experiment was conducted to see (1) how an agent considers five behaviors (adjust clothing level, adjust activity level, window use, blind use, and space heater/personal fan use behaviors) to achieve its comfort goal, and (2) how an agent adapts to the dynamic thermal changes in the space to optimize both comfort and energy savings.