Distributed demand response charging control of multiple plug-in electric vehicle clusters

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
IET Smart Grid Pub Date : 2023-08-07 DOI:10.1049/stg2.12124
Jie Yu, Jianqiang Hu, Cheng Li, Qingjie Zhang, Chuan Liu, Shidong Liu
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引用次数: 0

Abstract

This paper is devoted to the distributed demand response (DR) charging control of plug-in electric vehicles (PEVs) for frequency regulation in power systems in terms of load following service. Specifically, PEVs are divided into different clusters according to their parking place under different energy management systems. Each EV cluster is modelled by a transport-based load aggregate model with the input being the charging rate, and the output is the aggregate power. Based on the aggregate charging control model, a novel dynamic real-time distributed pinning control algorithm is proposed to coordinate the charging rates such that the aggregate charging power of PEVs can follow a given reference power trajectory. The theoretical analysis shows that if the reference power profile is in the trackable area of all PEVs' charging power and the ramping rate is restrained by a predefined bounded constraint, then the demand response charging tracking control is solvable. Finally, simulation results on an EV system with twelve PEV clusters are presented to show the effectiveness of the proposed demand response control algorithm.

Abstract Image

多插电式电动汽车集群分布式需求响应充电控制
本文致力于从负载跟随服务的角度研究用于电力系统频率调节的插电式电动汽车(PEV)的分布式需求响应(DR)充电控制。具体而言,在不同的能源管理系统下,电动汽车根据其停车位置划分为不同的集群。每个电动汽车集群都由基于交通的负载聚合模型建模,输入为充电率,输出为聚合功率。基于聚合充电控制模型,提出了一种新的动态实时分布式钉扎控制算法来协调充电速率,使PEV的聚合充电功率能够遵循给定的参考功率轨迹。理论分析表明,如果参考功率分布在所有PEV充电功率的可跟踪区域内,并且斜坡速率受到预定义的有界约束的约束,则需求响应充电跟踪控制是可解的。最后,对一个具有12个PEV集群的电动汽车系统进行了仿真,验证了所提出的需求-响应控制算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
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