This paper presents the equilibrium analysis of a game composed of heterogeneous electric vehicles (EVs) and a power distribution system operator (DSO) as the players, and charging station operators (CSOs) and a transportation network operator (TNO) as coordinators. Each EV tries to pick a charging station as its destination and a route to get there at the same time. However, the traffic and electrical load congestion on the roads and charging stations lead to the interdependencies between the optimal decisions of EVs. CSOs and the TNO need to apply some tolling to control such congestion. On the other hand, the pricing at charging stations depends on real-time distributional locational marginal pricing, which is determined by the DSO after solving the optimal power flow over the power distribution network. This paper also takes into account the local and the coupling/infrastructure constraints of EVs, transportation and distribution networks. This problem is modeled as a generalized aggregative game, and then a decentralized learning method is proposed to obtain an equilibrium point of the game, which is known as variational generalized Wardrop equilibrium. The existence of such an equilibrium point and the convergence of the proposed algorithm to it are proven. We undertake numerical studies on the Savannah city model and the IEEE 33-bus distribution network and investigate the impact of various characteristics on demand and prices.
翻译:本文介绍由不同电动车辆和电力分配系统操作员组成的游戏的均衡分析,该游戏由不同的电动车辆组成,电力分配系统操作员组成,充电站操作员和交通网络操作员担任协调员。每个电动车辆都试图选择充电站作为其目的地和同时到达该地点的路线。但是,道路和收费站的交通和电力负荷拥挤导致EV最佳决定之间的相互依存性。民间社会组织和TNO需要应用一些收费点来控制这种拥堵。另一方面,充电站的定价取决于实时分配地点边际定价,由DSO在解决电力分配网络的最佳电力流动之后确定。本文还考虑到EV、交通和配电网络的局部和组合/基础设施限制。这一问题以通用的聚合游戏为模型,然后提出一种分散学习方法,以获得游戏的平衡点,即所谓的变异式普遍战争平衡点。这种平衡点的存在由DSOO决定。S-EA的平衡点的存在以及拟议的城市价格的趋同性分析。我们用S-VANA的模型和S-VA的模型研究证明了S-VA值对它的影响。