Encouraging broader adoption of renewable energy sources is key to minimizing our dependence on the electric grid. Though installation of solar panels at homes is increasingly common, the process of managing the energy they generate is both manual and ad hoc. In this work, the PIs are building an infrastructure for data collection and analysis of energy generation, energy consumption, and user behavior in green homes; and an an integrated approach to green home energy management validated using a novel recommendation-based evaluation platform. Using a custom-built measurement infrastructure, the project conducts a broad study of homes powered by a variety of renewable sources. The study examines both energy generation by renewable sources as well as how and why energy is consumed by a variety of devices. The results inform the design of a holistic control system that matches predicted supply with demand of a distributed set of devices in the home. Moreover, the system is being deployed in a few homes and evaluated using a recommendation system implemented as a mobile application that suggests when users should run devices.
This project supports research critical to encouraging adoption of more environmentally responsible practices in the home and enables a collaboration between PI Banerjee, who teaches at an EPSCoR institution, and PI Rollins, who teaches at an undergraduate institution. Further, the project is developing a CS1 course that will increase awareness of green energy concepts by introducing computing through collection and analysis of data on energy consumption practices.