A simultaneous, multi-user, paired comparison test of communicating thermostats for task efficiency, preference, and perceived usefulness of advanced features.
A 2-year investigation of the effects of dynamic pricing, customer-programmed thermostat automation, utility-controlled thermostat automation, and real-time energy and cost information, on residential energy conservation, summer weekday peak reduction, and event-driven demand response.
Including: (1) Bill Impacts and Demographics (by rate), (2) Bill Impacts and Behavior (by rate), (3) Extrapolation of Savings Estimates to Population, (4) Baseline Calculation for Load Impact Evaluation (method comparison).
Results show that larger users respond more in both absolute and percentage terms, and customers in the coolest climate zone respond most as a percentage of their baseline load. Finally, an analysis involving the two different levels of critical-peak prices – $0.50/kWh and $0.68/kWh – indicates that households did not respond more to the higher CPP rate.
SMUD’s “Small Business Summer Solutions” pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. During the summer, participants had energy savings of 20%, and the potential for an additional 14% to 20% load drop during a 100°F demand response event. In addition to the efficiency-related bill savings, participants on the dynamic rate saved an estimated 5% on their energy costs compared to the standard rate.
Findings show that high-use customers respond significantly more in kW reduction than do low-use customers, while low-use customers save significantly more in percentage reduction of annual electricity bills than do high-use customers—results that challenge the strategy of targeting only high-use customers for CPP tariffs. Across income levels, average load and bill changes were statistically indistinguishable, as were satisfaction rates.
Hourly load data collected during a 15-month experiment shows statistically significant load reduction during events, for participants both with and without automated end-use control technologies. Response is greatest on days with maximum temperatures above 95°F, but good response is also found on days with maximum temperatures below 60°F.