Demand Response-Enabled Residential Thermostat Controls

Xue Chen, Jaehwi Jang, David M. Auslander, Therese Peffer, and Edward Arens, University of California, Berkeley

Keywords

Abstract

A number of Demand Response (DR) technologies work by responding to variable electricity pricing, but have not yet been applied to control residential HVAC systems. An autonomous thermostat system, the Demand Response Electrical Appliance Manager (DREAM), provides possibilities to improve price-based demand responsiveness in residences.

Built on low-cost, low-power wireless technology, the system uses a disaggregated set of energy- and environmental sensors. Control strategies are implemented to optimize electricity cost and user's comfort. To perform the optimization, the system starts from default values and learns the dynamic behavior of a house and HVAC system. A graphic user interface provides easy interaction with the system. Computer simulation, lab tests and field tests have been used to validate the system infrastructure and control strategies. These tests indicate that the DREAM responds automatically to price signals with appropriate energy saving behavior. The system can reduce electricity consumption during peak price hours without significantly decreasing comfort.