Abstract: The optimization model of electric vehicle, air conditioner, water-heater is instituted based on the household intelligent power utilization system, with the goal of economy and comfort. The particle swarm optimization based on Q-learning is used to solve the optimization model, so the intelligent power strategy of household electric appliances is solved. With the optimization model and the algorithm of air conditioner, and through the simulation experiment, the room temperature is controlled, the cost is least and the convergence rate is fast, so the electricity consumption of air conditioner load is reduced and the comfort of the consumer is guaranteed.

Key words: household appliances, optimization model, particle swarm optimization, Q-learning algorithm, household intelligent power utilization system

摘要： 在家庭智能用电系统下，以经济性和舒适性为目标，构建了电动汽车、空调、热水器的优化用电模型。并使用基于Q学习的粒子群算法求解优化模型，阐述家用电器的智能用电策略。以空调负荷为例，采用优化模型和算法后，经仿真实验，满足温度控制要求，且费用最少，收敛速度快，有效减少了空调负荷的用电量，削减电费的同时又保证用户的舒适度。

关键词: 家用电器, 优化模型, 粒子群算法, Q学习算法, 家庭智能用电系统