SBIR Phase I: Isolating Specific Appliance Energy Usage from Whole Building Energy Consumption

This Small Business Innovation Research Phase I project will test the feasibility of a signal processing algorithm to separate energy used by individual appliances from the total natural gas and electricity entering a home. Utility ratepayers may benefit from this detailed information by more-effectively identifying and mitigate inefficient appliances and activities. The new generation of smart electric meters currently being deployed for automated reading and time of use pricing are not be able to provide this level of detail. The signal processing algorithm evaluated in this study is innovative in its use of non-parametric statistical measures and specific conductance signatures to accurately distinguish individual appliance loads. Tests will be performed in three residences to compare the performance of the load disaggregation system with that of isolated electrical power measurements from ten or more appliances. The intended outcome of this project is to create an easy-to-use tool that will continually educate consumers to reduce energy consumption. When coupled with adoption of renewable energy sources, improving energy efficiency reduces greenhouse gas emissions. The commercial potential of this technology is high since residential and small business ratepayers could reduce energy costs if they can reliably identify inefficient appliances or activities. If successful, the energy savings from the average household using this technology would pay for the installed cost of the device in less than three years. Providing appliance specific level load information would transform ratepayers' ability to conserve energy and significantly impact resource consumption. This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).