电动汽车充电联合速率控制与需求平衡

Fanxin Kong, Xue Liu, Insup Lee
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引用次数: 10

摘要

充电站已经成为支持电动汽车快速发展不可或缺的基础设施。充电站的运行方案对满足电网的稳定性和电动汽车用户的服务质量至关重要。大多数现有计划的目标是两个主要操作中的一个:收费费率控制和需求平衡。这种片面的关注忽略了两种操作之间的耦合关系,从而导致电网稳定性或客户QoS的降低。一个深思熟虑的方案应该同时管理这两种操作。设计这种方案的一大挑战是它们的耦合关系所引起的聚合不确定性。这种不确定性从三个方面积累:与充电站共存的可再生能源发电机组、其他(或非电动汽车)消费者的电力负荷以及未来的充电需求。为了处理这种综合不确定性,我们提出了一种基于随机优化的操作方案。该方案将充电速率控制和需求均衡相结合,同时满足电网稳定性和用户QoS。此外,我们的方案由两种算法组成,我们分别为管理这两种操作而设计。我们的算法的一个吸引人的特点是,它们在这三个方面的预测误差方面有强大的性能保证。仿真结果证明了所提出的操作方案的有效性,并验证了理论结果。
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Joint Rate Control and Demand Balancing for Electric Vehicle Charging
Charging stations have become indispensable infrastructure to support the rapid proliferation of electric vehicles (EVs). The operational scheme of charging stations is crucial to satisfy the stability of the power grid and the quality of service (QoS) to EV users. Most existing schemes target either of the two major operations: charging rate control and demand balancing. This partial focus overlooks the coupling relation between the two operations and thus causes the degradation on the grid stability or customer QoS. A thoughtful scheme should manage both operations together. A big challenge to design such a scheme is the aggregated uncertainty caused by their coupling relation. This uncertainty accumulates from three aspects: the renewable generators co-located with charging stations, the power load of other (or non-EV) consumers, and the charging demand arriving in the future. To handle this aggregated uncertainty, we propose a stochastic optimization based operational scheme. The scheme jointly manages charging rate control and demand balancing to satisfy both the grid stability and user QoS. Further, our scheme consists of two algorithms that we design for managing the two operations respectively. An appealing feature of our algorithms is that they have robust performance guarantees in terms of the prediction errors on these three aspects. Simulation results demonstrate the efficacy of the proposed operational scheme and also validate our theoretical results.
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