Impact of Social Network Type and Structure on Modeling Normative Energy Use Behavior Interventions

Abstract

Occupant behavior has a substantial impact on the total energy consumption in buildings. To reduce consumption much work has been done investigating behavioral energy-use interventions (e.g., feedback). Being able to accurately identify effective interventions for specific buildings or communities of buildings based on local conditions has significant implications for reducing energy consumption and demand in buildings. Therefore, recently researchers have begun developing predictive models of these behavioral interventions. However, limited consideration has been given to the importance that modeling assumptions (regarding social network type and structure) have in determining impact on intervention outcome. In this paper, an integrated model that combines established social-psychological principles of social influence and cultural norm diffusion with building social network profiles is developed and tested to examine the effect of social network type and structure on interventions. The writers apply agent-based modeling to simulate the interactions of heterogeneous building occupants in their respective social networks to examine the importance of social network type and structure for two interventions, as follows: (1) installing a peer energy-use feedback system, and (2) installing a feedback system and inserting an intervening agent into the building. The results indicate that network type and structure can have a significant effect on the time required for occupant energy-use intervention outcomes to reach a state of equilibrium. Thus, when modeling and selecting behavioral interventions, expected interventions outcomes should not be assumed based solely on generalized results from other studies, but consideration must be given to specific social network properties.