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首页> 外文期刊>Smart Grid, IEEE Transactions on >Charging Strategies of EV Aggregator Under Renewable Generation and Congestion: A Normalized Nash Equilibrium Approach
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Charging Strategies of EV Aggregator Under Renewable Generation and Congestion: A Normalized Nash Equilibrium Approach

机译：可再生发电和交通拥堵下的电动汽车聚合器充电策略：归一化纳什均衡法

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摘要

This paper proposes a two-stage charging scheme for the electric vehicle aggregator to minimize the charging cost of each individual participator, while taking uncertain renewable generation and aggregator’s capacity into account. The charging problem is formulated as a generalized Nash game with shared global constraints, where the congestion constraint and renewable energy utility constraint that couple all participators’ strategies serve as the global constraints and should be satisfied for all possible outcomes of uncertainty. The normalized Nash equilibrium (NNE) is used to characterize a fair charging decision among the participants. It is shown that when the commission fee charged by the aggregator is a convex function and proportionally shared by the consumers, the NNE can be efficiently computed from a particular convex optimization problem, and is noninferior if the commission fee function is separable in players. An adaptive scenario generation algorithm is developed to solve the proposed model in a tractable manner. A dynamic real-time bidding scheme is suggested for practical implementations in a receding horizon fashion, accounting for tackling various kinds of uncertainties. Numerical results are presented to corroborate the proposed technique.
机译：本文提出了一种针对电动汽车聚合器的两阶段充电方案，以最大程度地降低每个单独参与者的充电成本，同时考虑到不确定的可再生能源发电和聚合器的容量。充电问题被公式化为具有共享全局约束的广义Nash博弈，其中将所有参与者的策略结合在一起的拥塞约束和可再生能源效用约束充当全局约束，并且对于所有不确定性结果都应满足。归一化的纳什均衡（NNE）用于表征参与者之间的公平计费决策。结果表明，当集合商收取的佣金费用是凸函数并由消费者按比例分配时，可以从特定的凸优化问题中有效地计算出NNE，并且如果参与者之间的佣金函数是可分离的，则NNE也不差。提出了一种自适应场景生成算法，以一种易于处理的方式来解决所提出的模型。为了解决各种不确定性，建议以一种动态的实时出价方案来以渐进的方式实际实施。数值结果表明了所提出的技术。

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