Automating energy management in green homes

Homes powered fully or partially by renewable sources such as solar are becoming more widely adopted, however energy management strategies in these environments are lacking. This paper presents the first results of a study that explores home automation techniques for achieving better utilization of energy generated by renewable technologies. First, using a network of off-the-shelf sensing devices, we observe that energy generation and consumption in an off-grid home is both variable and predictable. Moreover, we find that reactive energy management techniques are insufficient to prevent critical battery situations. We then present a recommendation based system for helping users to achieve better utilization of resources. Our study demonstrates the feasibility of three recommendation components: an early warning system that allows users of renewable technologies to make more conservative decisions when energy harvested is predicted to be low; a task rescheduling system that advises users when high-power appliances such as clothes dryers should be run to optimize overall energy utilization; and an energy conservation system that identifies sources of energy waste and recommends more conservative usage.