由于可再生能源电源和电动汽车的急速发展和其可观的环境效益,越来越多的可再生能源和电动汽车接入到配电网中.由于可再生能源和电动汽车的随机不确定性,电力特性发生改变,导致配电网的安全性和经济性降低.因此,为使电网更加经济,储能技术在调节系统功率方面受到越来越多的关注.该文提出含可再生能源电源的配电网中储能和电动汽车运行调度优化模型,以减小损耗,改善电压分布,从而使储能或电动汽车聚合商效益最大化.为得到最优调度,提出3种基于粒子群算法的约束策略,包括死区约束、充放电周期约束和充放电功率优化.最后,采用IEEE 33节点配电网系统进行仿真,验证所提方法的有效性.结果表明,该方法在降低网络损耗的同时,降低了电池的运行成本.“,”More and more renewable energy sources (RESs) and electric vehicles (Evs) have become part of the distribution network due to their rapid development and considerable environmental benefits. Because of the randomness and uncertainty of renewable energy and Evs, the electric power characteristics have been changed and the active power losses are increased, which decreases the safety and economics of the distribution network. Therefore, energy storage (ES) is given significant attention for regulating system power in order to make the network more economical. In this paper, the operational schedule optimization model of ES and Evs in the distribution network with RESs was proposed to diminish losses, improve voltage profile and maximize the benefits of the ES\'s or EVs\' aggregator. In order to obtain the optimal schedule, three constraint strategies based on the particle swarm optimization (PSO) algorithm were proposed, including dead-time constraint, charging and discharging cycles constraint, and charging and discharging power optimization. Finally, a simulation of an IEEE 33-node distribution network was carried out to examine the effectiveness of the proposed approach. The results show that the network losses are reduced while the operating cost of the battery is decreased by using the method proposed in this paper.