A Particle Swarm Optimization and Branch and Bound Based Algorithm For Economical Smart Home Scheduling

摘要

Smart home scheduling, as one of the most effective techniques in Demand Side Management (DSM), is now attracting more and more research interests in the recent years. In this paper we propose an efficient scheduling algorithm for smart home resident to reduce the monetary cost of the electricity. The proposed algorithm is an improved particle swarm optimization (PSO) algorithm that can schedule the smart appliances under discrete power level and quadratic pricing model. Branch and bound method is adopted to map real number values to discrete power level values. Simulation results shows that our method exceeds the previous methods both in total monetary cost and execution time.