首页> 外文会议>IEEE Transportation Electrification Conference and Expo Asia-Pacific >Intelligent charging strategy for PHEVs in a parking station based on Multi-objective optimization in smart grid
【24h】

Intelligent charging strategy for PHEVs in a parking station based on Multi-objective optimization in smart grid

机译:基于智能电网中多目标优化的停车场PHEV智能充电策略

获取原文

摘要

With the increasing popularity of Plug-in Hybrid Electric Vehicles (PHEVs), the public charging infrastructure construction such as charging station and PHEV charging enabled parking station has also appeared. The problem of scheduling large-scale of PHEVs in such centralized charging infrastructure should be considered to avoid adverse effects on the power system because of their uncontrolled charging. For example, lots of PHEVs' charging simultaneously at period of peak-load may pose a wide pressure on the grid's peak regulation. In this paper, an intelligent charging strategy which can decide each PHEV's charging power at each time step is proposed for a cluster of PHEVs in a parking station based on time of use (TOU) price. A mathematic optimal model with the muti-objective function (i.e. minimizing the charging cost and minimizing load variance) is also given considering several constraints such as the chargers' power limit and charging efficiency. The proposed strategy only considers PHEVs as controllable load, but it's also applicable to situations where other controllable load are added in the future. In this paper, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the optimization problem and the matlab calculation results validate the effectiveness of the proposed strategy.
机译:随着插电式混合动力汽车(PHEV)的日益普及,诸如充电站和启用PHEV充电的停车站之类的公共充电基础设施建设也已出现。应该考虑在这种集中式充电基础设施中安排大型插电式混合动力汽车的问题,以避免由于其不受控制的充电而对电力系统造成不利影响。例如,许多PHEV在峰值负荷时段同时充电可能会对电网的峰值调节造成很大压力。在本文中,提出了一种智能充电策略,该策略可以根据使用时间(TOU)价格为停车场中的一组PHEV提出一个可以确定每个时间步长的每个PHEV充电功率的策略。考虑到充电器的功率极限和充电效率等若干约束条件,还给出了具有多目标函数(即最小化充电成本和最小化负载变化)的数学最优模型。提出的策略仅将PHEV视为可控负载,但也适用于将来添加其他可控负载的情况。本文采用非支配排序遗传算法II(NSGA-II)解决了优化问题,并通过matlab计算结果验证了该策略的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号