This paper describes a computational platform for studying the effects of price-responsive residential demand for air-conditioning (A/C) on integrated retail and wholesale power market operations. The physical operations of the A/C system are represented by means of the physics-based equivalent thermal parameter model. Residential A/C energy usage levels are determined by means of a stochastic dynamic-programming optimization in which the daily comfort attained by the resident is optimally traded off against his daily energy costs, conditional on retail energy prices, environmental conditions, and A/C operational constraints. An example is provided to illustrate the dynamic feedback loop connecting residential A/C load, the energy prices determined at wholesale conditional on A/C load, and the retail energy prices offered to residential A/C consumers by wholesale energy buyers.