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Charging station selection and charging price decision for PEV: A two level game approach

机译:PEV的充电站选择和充电价格决定:两级博弈方法

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In this paper, we consider the problem that a group of plug-in electric vehicles (PEVs) seek to maximize their payoff by selecting a proper charging station and the charging stations try to maximize their revenue by adjusting the electricity price according to the total demands they received. Since both the decisions of the charging stations and the PEVs should be made dynamically under competition environments, we propose a two-level game framework to model this issue. At the lower level, the PEVs need to adapt their strategies, i.e. the charging station selection, according to the service they can get from each charging station, and we formulate it as an evolutionary game and use replicator dynamics to model the charging station selection process. Also, we propose an algorithm to arrive at the evolutionary equilibrium. At the upper level, each charging station needs to set the electricity price appropriately to maximize its revenue according to the received total amount of electricity requirement from PEVs. We formulate a differential game to describe the competition among the charging stations and analyze the Nash equilibrium for both open-loop strategies and closed-loop strategies. Simulation results demonstrate that the proposed mechanism can gain a higher profit and faster convergence speed than static control.
机译:在本文中,我们考虑了一组插电式电动汽车(PEV)试图通过选择合适的充电站来最大化其收益,并且充电站试图通过根据总需求调整电价来最大化其收益的问题。他们收到了。由于充电站和PEV的决策都应在竞争环境下动态做出,因此我们提出了一个两级博弈框架来对此问题进行建模。在较低级别,PEV需要根据其从每个充电站获得的服务来调整其策略,即充电站选择,我们将其公式化为演化博弈,并使用复制器动力学来建模充电站选择过程。此外,我们提出了一种算法来达到进化均衡。在上层,每个充电站都需要根据从私家电动车收到的总电量需求,适当地设定电价,以最大程度地增加其收入。我们制定了一个差分博弈来描述充电站之间的竞争,并针对开环策略和闭环策略分析了纳什均衡。仿真结果表明,与静态控制相比,该机制具有更高的收益和更快的收敛速度。

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