Skip to Main Content
With the development of demand side management for future smart grid applications, residential loads are expected to provide elastic response to fluctuating generation. The smart meter of a household can implement such functionality by using various control schemes or algorithms developed to schedule the use of residential loads with optimal customer and utility benefits. In this paper, the energy consumption of an air conditioner is modeled as a function of temperature, and the relationship between the energy cost and the temperature set-point is investigated. Then, to maximize the customer's benefit, a schedule optimization algorithm, using best response technique, is proposed. The performance and improvement of this algorithm are evaluated at the end of the paper.