Optimal Home Energy Management for Smart Home using Random Bit Climbing

Home Energy Management Systems (HEMS) has been considered to manage the energy usage at smart homes. In this paper, Optimal Home Energy Management (OHEM) algorithm is introduced to select the time slots, at which the electrical tasks are executed so that the electric power cost and the user comfort are improved. Random Bit Climbing (RBC) optimization method is employed to get an optimal or near-optimal solution that represents the time slots of the home tasks operation. Real-Time Pricing (RTP) is considered for electricity cost. Firstly, the electrical tasks are modeled to determine its main attributes. The objective function of the proposed algorithm is defined as a utility function that minimizes the user conform and the electricity cost. After that, the RBC method is performed to get the optimal or near-optimal solution that minimizes the objective function.Simulation results show that the proposed OHEM algorithm improve the electrical energy cost with reasonable user comfort. Additionally, the degree of improvement for electrical energy cost and user comfort can be adjusted and controlled using a weighting parameter.