Optimizing Electric Vehicle Charging: A Customer's Perspective
Optimizing Electric Vehicle Charging: A Customer's Perspective
复制标题
DOI：
10.1109/tvt.2013.2251023
复制
发表时间：
2013-03
影响因子：
6.8
通讯作者：
Chenrui Jin;Jian Tang;P. Ghosh
中科院分区：
文献类型：
--
作者：
Chenrui Jin;Jian Tang;P. Ghosh
电动汽车(EVS)被认为是解决当前汽油短缺和排放问题的一种有前途的解决方案。为了最大限度地发挥使用电动汽车的好处，联网车辆的负载聚合器需要提供规范和优化的充电控制。电动汽车充电网络是一个典型的网络物理系统，它包括一个电网和大量的电动汽车以及收集信息和控制充电过程的聚合器。本文从用户的角度出发，综合考虑集电商的收益和用户的需求和成本，研究了电动汽车充电调度问题。我们考虑了两种充电方案：静态和动态。在静态充电场景中，客户的充电需求是提前提供给聚合器的；而在动态充电场景中，电动汽车随时可能来去自由，这是聚合器事先不知道的。对于静态问题，我们提出了基于线性规划(LP)的优化方案；对于动态问题，我们提出了有效的启发式算法。动态情景更现实；然而，静态问题的解决方案可以用来显示受监管的收费可以带来的潜在收入收益和成本节约，因此可以作为业绩评估的基准。基于实际电价和负荷数据的大量仿真结果表明，与不受管制的基线方法相比，最优充电调度方案可以获得显著的收入收益和成本节约，而且所提出的动态充电调度方案提供了接近最优的解。
Electric vehicles (EVs) are considered to be a promising solution for current gas shortage and emission problems. To maximize the benefits of using EVs, regulated and optimized charging control needs to be provided by load aggregators for connected vehicles. An EV charging network is a typical cyber-physical system, which includes a power grid and a large number of EVs and aggregators that collect information and control the charging procedure. In this paper, we studied EV charging scheduling problems from a customer's perspective by jointly considering the aggregator's revenue and customers' demands and costs. We considered two charging scenarios: static and dynamic. In the static charging scenario, customers' charging demands are provided to the aggregator in advance; however, in the dynamic charging scenario, an EV may come and leave at any time, which is not known to the aggregator in advance. We present linear programming (LP)-based optimal schemes for the static problems and effective heuristic algorithms for the dynamic problems. The dynamic scenario is more realistic; however, the solutions to the static problems can be used to show potential revenue gains and cost savings that can be brought by regulated charging and, thus, can serve as a benchmark for performance evaluation. It has been shown by extensive simulation results based on real electricity price and load data that significant revenue gains and cost savings can be achieved by optimal charging scheduling compared with an unregulated baseline approach, and moreover, the proposed dynamic charging scheduling schemes provide close-to-optimal solutions.