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As more renewable energy sources are added to the grid, balancing power demand with generation will become increasingly difficult for grid operators. A promising solution to this issue, Automated Demand Response (ADR) technology, which seeks to intelligenly alter the power demand, providing grid operators with an easier to serve energy demand pattern. As a result of this, operation costs for both the end-consumer and the utility can be reduced, peak grid demands can be lowered, and the necessity of environmentally damaging peaker plants can be lowered.
To that end, this project is an iteration on a previous smart-home testbed platform which seeks to demonstrate the effectiveness of ADR technology. In this iteration of the testbed, we seek to simulate residential-scale power generation via solar, residential-scale energy storage via battery, as well as common home energy consumption loads such as lighting and air conditioning. This project also implements an observation and control website to facilitate remote operation of the test bed, intelligent ADR control algorithms for the aforementioned loads, and centralized data collection and analysis.
- Josh Chambers (Team Lead & EE Lead)
- William Winslade (Software Lead)
- Sally Grigsby (Software)
- Justin Proctor (EE)
- Ethan Durham (EE)
- Joe Curatolo (EE)