考虑电力-交通耦合网动态协调的EV集群灵活性挖掘与优化调度

Flexibility Mining and Optimal Scheduling for Electric Vehicle Clusters Considering Dynamic Coordination of Power-Transportation Coupling Network

电动汽车(EV)作为兼具交通与能量双重属性的跨域主体,发挥其时空灵活性将助力电力-交通耦合网的协调运行。为此,文中考虑电力-交通耦合网综合效益,提出了EV集群调控策略。首先,基于弧阻抗函数构建了动态交通网络加载模型。其次,考虑EV用户的各特征参数存在的差异性与耦合性,构建了单体EV灵活运行域模型,并采用基于zonotope线性近似的闵可夫斯基和算法对其聚合,得到EV集群的时变灵活运行域。在此基础上,提出了动态交通流最优分配下EV集群灵活性调控的双层模型,迭代求解得到上下两层耦合变量构成的瞬时单位流量出行成本,从而引导EV的出行与充放电行为。最后,通过与最短路径引导策略进行比较,验证了所提EV集群调控策略的有效性。

As a cross-domain subject with both transportation and energy attributes,electric vehicles(EVs)can exert their spatiotemporal flexibility to help the coordinated operation of the power-transportation coupling network.Therefore,a scheduling strategy for EV clusters considering the comprehensive benefits of power-transportation coupling network is proposed.First,a dynamic transportation network loading model is constructed based on arc impedance function.Then,considering the difference and coupling of the characteristic parameters of EV users,the flexible operation domain model of individual EV is constructed.Based on the Minkowski sum algorithm under the linear approximation of zonotope,the time-varying flexible operation domain of EV clusters is obtained.On this basis,a two-layer model for flexibility scheduling of EV clusters under optimal assignment of dynamic traffic flow is proposed,and the instantaneous travel cost of unit flow composed of the coupling variables of the upper and lower layers is obtained through iterative solution,which can guide the traveling and charging/discharging behaviors of EVs.Finally,the validity of the proposed scheduling strategy for EV clusters is verified by comparing it with the shortest path guidance strategy.