Appliance scheduling in a smart home using a multiobjective evolutionary algorithm

In this paper, we propose a multiobjective evolutionary algorithm to solve the appliance scheduling problem in a smart home in a one-day horizon subdivided into 1440 time slots of one minute each. Mathematically, the appliance scheduling problem is formulated as an integer programming problem in which the decision variables consist of finding the optimal starting times of appliances under a time-varying electricity prices and the time windows in which the appliances must be operated. The aim is to minimize the two conflicting objectives simultaneously: The electricity cost and the discomfort caused by the delay or the advance of the appliances starting times from the preferred starting times set by a home consumer. The extreme solutions of the obtained pareto front; best cost solution and best discomfort solution, are compared with the reference case in which a home consumer starts his/her appliances on his/her preferred starting times. The simulation results show that the ability of the proposed algorithm to shift appliances consumption in response to time-varying electricity prices from the on-peak price periods to the off-peak price periods within the time windows of appliances, through which a home consumer may reduce electricity cost without a significant impact on his/her comfort.