基于模糊逻辑的智能充电网络电动汽车调度

Jinsol Park, Yujin Sim, Gangminh Lee, D. Cho
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引用次数: 10

摘要

为了显著提高智能充电网络的充电性能,提出了一种基于模糊逻辑控制的电动汽车调度算法。模糊逻辑控制有助于电动汽车调度算法从逻辑上确定合适的充电站和电动汽车对。模糊推理系统通过反映电动汽车与汽车之间的距离、充电时间、充电速度等多种充电要求,确定一个权重值。权重值描述了电动汽车充电的优先级,并用于调度算法。本文提出的调度算法主要通过减少充电等待时间和平衡充电请求率来避免电动汽车在CS处的拥塞,从而在平衡可用充电垫数量的情况下将电动汽车分配给CS。为了与传统调度算法的性能进行比较,本文还考虑了随机调度算法和最大权值调度算法。仿真结果表明,从充电等待时间和充电请求率的平衡两方面考虑,所提出的调度算法能够提高智能充电网络的性能。
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A Fuzzy Logic Based Electric Vehicle Scheduling in Smart Charging Network
This paper proposes an electric vehicle (EV) scheduling algorithm with fuzzy logic control in smart charging network in order to improve the charging performance of the network significantly. The fuzzy logic control helps that the EV scheduling algorithm determines the proper pair of charging station (CS) and EV logically. The fuzzy inference system determines a weight value by reflecting the multiple charging requirements such as distance between EV and CS, charging time, and charging speed. The weight value describes an EV charging priority, and is used in the scheduling algorithm. The proposed scheduling algorithm focuses on avoiding EV congestion at the CS by reducing the waiting time for charging and balancing charging request rate, which shows how the EV is distributed to the CS with balancing the number of available charging pads. In order to compare the performance of the proposed scheduling algorithm with that of conventional algorithms, the random and max weight scheduling algorithm are also considered. The simulation results show that the proposed scheduling algorithm can improve the performance of the smart charging network in view of waiting time for charging and balancing of charging request rate.
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