Disaggregating End Loads with Energy-Harvesting Sensors and Cloud Analytics

Abstract

Obtaining a detailed breakdown of household energy consumption would allow occupants to better understand their energy usage patterns and identify opportunities for energy savings. Current solutions are too course-grained, too difficult to deploy, not networked, or offer poor coverage of hard to meter items, such as ceiling lights. To address these problems, we demonstrate a wirelessly networked, energy-harvesting power metering system that draws zero standby power and is power proportional to the load it is metering. The system is comprised of three different meters: one for plugged-in loads, one for panel-level circuits, and one for hard-to-sense loads, such as ceiling lights. Each meter harvests energy proportionally to the load it is measuring and powers a sensor node intermittently. Together, these sensors create multiple data streams which are aggregated by a receiver. When combined with a calibrated meter that measures total household power, our system can iteratively determine the contributions of each load to the total power usage, allowing users to gain a broad yet detailed view of their energy consumption and costs.