This report presents results from field testing and comfort surveys designed to evaluate peak demand-limiting strategies that utilize both precooling and adjustments of zone cooling setpoints. The testing was performed over a two-week period at a small bank building in Palm Desert, California. During the first week test, three kinds of control strategies were considered: 1) conventional night setup control as a baseline case, 2) a simple linear-rise demand-limiting strategy that involved precooling during the morning and linear setpoint adjustments during an afternoon demand-limiting period, and 3) a simple step-up demand-limiting strategy that included precooling in the morning and resetting of setpoint during the demand-limiting period.

During the second week of testing, a demand-limiting strategy was tested for four days with setpoint trajectories determined using a weighted-averaging method developed at Purdue University. Precooling of the building was performed at 70ºF setpoint from 6am to 12pm and setpoints during the on-peak period from 12pm to 6pm were modulated from 70 to 78ºF following a trajectory that attempted to minimize peak cooling load. (The measured temperature at the polling station was a minimum of 1.5 degrees F above the thermostat setpoint (see figures 24 to 29 in appendix). The baseline was conventional night-setup control with a 72ºF cooling setpoint temperature during the occupied period. The demand-limiting tests resulted in greater than 30% reduction of peak air conditioner power on average for the four tested days which accounted for 0.76W/ft2 peak savings. 

The comfort survey revealed that the response of occupants was highly variable at any given indoor temperature. Statistical analysis of all the data collected, including baseline days and test days, indicated a significant probability that a given occupant will vote that the temperature is ‘cool’ at the low setpoint temperature of 70 degrees (between 30 and 50 percent), and ‘warm’ at the upper setpoint of 78 degrees (between 37 and 52 percent) (figure 21). However, only half of these votes are at the level where the ii respondent says it ‘bothers’ them. The probability of a given occupant being bothered by the ‘cool’ temperature at the low setpoint is estimated to be 17 percent and the probability of a given occupant being bothered by the ‘warm’ temperature at at the upper setpoint is estimated to be 23 percent. (figure 22). If we assume the neutral temperature to be between 74 and 75 degrees F, the probability of dissatisfaction (both ‘Too warm! It bothers me’ and ‘Too cool! It bothers me’) is estimated to be 20 percent.