基于磷虾群算法的并网电动汽车功率优化分配

为提高并网电动汽车(EV)集群的功率优化分配效率,提出基于磷虾群算法的EV集群并网两阶段功率高效分配策略。考虑用户的需求差异,将并网EV细化为不可调度集及可调度集,分别建立充放电控制模型,提出可调度集EV的优先权评估指标。采用动态自适应权重策略及余弦递减步长演进策略改进磷虾群(KH)算法,将可调度集EV的优先权映射为迭代算法的演变步长,通过两阶段交互迭代实现并网EV集群的功率高效分配。仿真实验验证了模型的可行性以及所提策略的高效性。

Power optimization allocation for grid-connected EV based on krill herd algorithm

To improve the optimal power allocation efficiency of grid-connected electric vehicles(EV),a two-stage power allocation strategy based on krill herd(KH)algorithm was proposed.Considering the demands difference of users,the grid-connected EV was divided into non-schedulable set and schedulable set,the charging-discharging control model was established,and the priority evaluation index of EV in schedulable set was proposed.The dynamic adaptive weight strategy and cosine decreasing step evolution strategy were adopted to improve the KH algorithm,and the priority of EV in schedulable set was mapped to the evolution step of the iterative algorithm.The feasibility of the model and the efficiency of the proposed strategy were verified by simulation results.