Explanations of widespread disengagement with energy use often rest on the belief that energy behavior is rooted in individuals' concerns about the environment and/or costs of energy. Missed in these explanations is the need to understand and address sociological and psychological factors in energy behavior. This project employs a series of energy use interventions in the community of Fremont, California, engaging children, youth and their families in this community. The interventions take advantage of new smart grid technologies, in particular, high-resolution energy data now available via smart metering and increasingly smart devices and appliances. Novel data-driven understandings of energy behavior will permit segmenting households according to their energy-use lifestyles. A novel intertwining of revealed lifestyle patterns from high-resolution data, data-driven tailored feedback, and community-based interventions has the potential to attract the hearts and minds of households and community members in ways that economic and environmental concerns cannot.

The community interventions will be child- and youth-focused and delivered at multiple levels, with: (1) data-driven visualizations and messages to participants via mobile applications; (2) an in-depth, multi-session intervention with local Girl Scout troops that encourages engagement with real-time smart meter energy data, devices and appliances; (3) a competition among local high schools to encourage widespread energy engagement and savings; (4) community meetings led by trained community college students adapted from Deliberative Polling® techniques; (5) sophisticated analytics of lifestyle and network effects; and (6) optimization modeling to better understand future load flexibility with behavioral modifications. Smart meter data on household energy use will be the main outcome of interest. Randomized experiments and participant surveys will also be used to gauge the program's effectiveness. We will thus combine the best practices of big data analytics and visualization from engineering with community-engaged intervention strategies from the behavioral sciences to enhance our knowledge of the potential pivotal role of big data, social science theory, and community-based methods in transforming local energy management and consumption today and in the future.