Abstract: This paper proposes a home energy management mechanism for residential demand response and formulates a stochastic optimal scheduling model aimed to minimize expected electricity costs by coordinating controllable appliances, electric vehicles, energy storage systems, and uncertainties in solar generation and uncontrollable loads. A mixed optimization algorithm combining binary particle swarm optimization (BPSO) and the interior point (IP) method is adopted to solve the model; this employs BPSO to handle discrete variables and the IP method to tackle continuous variables, which thus overcomes the weakness of BPSO in handling complex equations and inequation constraints. Simulation results show that the proposed optimization model and algorithm can reduce the effect of randomness on scheduling results and assist in reudcing electricity costs for residential customers.