A simulated annealing algorithm for demand response

For many consumers there are loads which need to be on for a subinterval between two time instants, but it is immaterial during which subinterval it is run. In many price based Demand Response (DR) programs such as Time of Use (TOU), Critical Peak Pricing (CPP), Extreme Day Pricing customers are informed about the prices on a day ahead bases. By scheduling the subintervals during which the loads are used consumers can minimize their electricity bill and by so doing the maximum demand on the system will decrease. This paper formulates this as an optimization problem and a simulated annealing based algorithm is used to find the optimum schedule. The algorithm is scalable and is applicable to a broad category of loads.