Through a class of computational models, agent-based modeling (ABM) is able to simulate the interaction of autonomous agents or organizations with a view to assessing their effects on the system as a whole. The global behavior and pattern will emerge as a result of interactions of many individual behaviors. ABM is a suitable tool to study complex engineering systems.
This research aims to understand, improve and predict the energy dynamics that occur in networks of building occupants. If occupants in these networks can view energy utilization of their own and their peers, they may change their energy using patterns. Four energy utilization experiments in residential and administrative buildings have been performed to empirically assess and model the complex inter-relationships between occupants and occupant networks in influencing energy use decisions. The experimental results were integrated into an agent-based simulation model to predict the impact of building occupant network dynamics on achieving sustained energy conservation in and across buildings.