Block Configuration Modeling: A novel simulation model to emulate building occupant peer networks and their impact on building energy consumption

Recent research has shown that providing building occupants with eco-feedback regarding their own energy consumption and the consumption of others in their peer network can lead to substantial energy savings. While empirical eco-feedback studies have provided valuable insights into the dynamics of energy consumption behavior and building occupant peer networks, such studies have faced challenges in examining consumption behavior in larger and more complex peer networks. Computer simulation and random network models offer a solution to this scalability issue, but current random network models are limited in their ability to mimic real world building occupant networks. In this paper, we propose a refined random network model, the Block Configuration Model, and utilize it in an agent-based energy consumption simulation. Results indicate that the Block Configuration Model is more accurate than conventional models when compared to empirical data from three different eco-feedback experiments. The Block Configuration Model advances our understanding of the dynamics of occupant energy consumption and provides a tool to reduce energy consumption and associated emissions.

► We propose the Block Configuration Model (BCM) to simulate occupant peer networks.
► Detailed algorithm and theoretical basis for the BCM is provided.
► We utilize the BCM in an agent-based energy consumption behavior simulation.
► The BCM is more accurate than conventional models in simulating energy consumption.
► Results advance our understanding of the dynamics of occupant consumption behavior.