Routinely encouraging and discouraging residential electric load throughout the day will be increasingly crit-ical in efficiently managing the smart grid to reliably de-liver clean, low-cost electricity. Yet, manipulating the duty cycles of thermostatically controlled loads such as heating, air conditioning, and hot water heaters can have the effect of destabilizing or stabilizing the grid. This work explores the potential for price-responsive control of residential air conditioning to shape electric demand at the distribution feeder level to minimize electricity production costs. Physical models of the interplay be-tween building thermal and electric loads are used to simulate time-series temperature and load behaviour. In-stantaneous load-adding and load-shedding opportuni-ties are quantified in more than 100,000 individual homes on 204 distribution feeders with results presented for 35 cities across the United States. In the context of distributed model predictive control, simulation of feeder-level response to a residential day-ahead 5-mi-nute pricing vector to 2,146 homes highlights an aggre-gate impact of flexible loads.</p
