基于半动态交通流模型的电动汽车出行引导策略

Electric Vehicles Travel Guidance Strategy Based on Semi-dynamic Traffic Flow State Model

为综合考虑电网和交通网的运行,优化电动汽车出行并实现充电控制,基于半动态交通流模型的特征和累积前景理论,提出了一种考虑电动汽车出行决策效用的出行引导策略。首先,计及用户的有限理性,基于改进的累积前景理论,建立电动汽车出行决策效用模型;基于此,提出用户出行引导策略以及与用户的前景函数形式和出行决策效用紧密相关的半动态交通流模型,实现交通平衡配流;进一步地,充分考虑用户的异质性和自主性,分析出行引导策略下的电动汽车(electricvehicle,EV)出行决策与充电功率随机性的关系,建立分布鲁棒优化的充电功率控制模型。最后,通过电网–路网耦合系统的仿真,验证了所提电动汽车出行引导与充电控制优化策略的有效性,结果表明所提电动汽车出行引导策略不仅能够降低交通拥堵概率和电动汽车出行耗电量,还能降低电网峰谷差,实现电网与交通网协同运行。

In order to comprehensively consider the operations of power grids and transportation networks,and optimize the electric vehicles(EVs)’traveling and charging control,an EV travel guidance strategy considering the decision utility model is proposed based on the characteristics of the semi-dynamic traffic flow state model and the cumulative prospect theory.First,an EV travel decision utility model is established based on the improved cumulative prospect theory considering the finite rationality of the user's travel decision.On this basis,a user travel guidance strategy and a semi-dynamic traffic flow model closely related to the user's cumulative prospect function and travel decision utility are proposed to realize the traffic balance distribution flow.Further,with a full consideration of the heterogeneity and autonomy of the users,the relationship between the EV travel decision and charging power randomness under the travel guidance strategy is analyzed,and a distributed robust optimal charging power control model is constructed.Finally,through the simulation of the power grid-road network coupling system,the effectiveness of the proposed travel guidance strategy and charging control optimization mode is verified.The results show that the EV travel guidance and charging strategy proposed can not only reduce the probability of traffic congestion and the power consumption of EV traveling,but also reduce the peak-valley differences of power grids and realize the coordinated operation of the power grids and the transportation networks.