首页 | 本学科首页   官方微博 | 高级检索  
     

交直流配电网中电动汽车充换储一体站规划
引用本文:曾梦隆,韦钢,朱兰,袁洪涛,何晨可,马钰. 交直流配电网中电动汽车充换储一体站规划[J]. 电力系统自动化, 2021, 45(18): 52-60. DOI: 10.7500/AEPS20210112007
作者姓名:曾梦隆  韦钢  朱兰  袁洪涛  何晨可  马钰
作者单位:上海电力大学电气工程学院,上海市 200090;华东电力设计院有限公司,上海市 200001;华南理工大学电力学院,广东省广州市 510640
基金项目:国家自然科学基金青年基金资助项目(51807114)。
摘    要:首先,以马尔可夫和速度-流量模型对快充车辆和电动公交进行时空负荷预测,结合快充站、换电站和梯级储能站的充放电功率构建充换储一体站(CSSIS)模型.然后,建立含CSSIS的交直流潮流模型,构建计及电动汽车到站行驶时间、排队等待时间和交直流配电网电压偏差的多目标选址模型,采用动态权重结合二进制遗传算法进行求解.其次,采用...

关 键 词:交直流配电网  电动汽车  充换储一体站  多目标规划
收稿时间:2021-01-12
修稿时间:2021-03-18

Planning of Electric Vehicle Charging-Swapping-Storage Integrated Station in AC/DC Distribution Network
ZENG Menglong,WEI Gang,ZHU Lan,YUAN Hongtao,HE Chenke,MA Yu. Planning of Electric Vehicle Charging-Swapping-Storage Integrated Station in AC/DC Distribution Network[J]. Automation of Electric Power Systems, 2021, 45(18): 52-60. DOI: 10.7500/AEPS20210112007
Authors:ZENG Menglong  WEI Gang  ZHU Lan  YUAN Hongtao  HE Chenke  MA Yu
Affiliation:1.College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.East China Electric Power Design Institute Co., Ltd., Shanghai 200001, China;3.School of Electric Power, South China University of Technology, Guangzhou 510640, China
Abstract:First, this paper uses the Markov and velocity-flow models to predict the space-time load of fast-charging vehicles and electric buses. The charging and discharging power of fast-charging stations, switching stations and cascade energy storage stations are combined to construct the charging-swapping-storage integrated station (CSSIS) model. Then, a power flow model of AC/DC with CSSIS is established, and a multi-objective siting model that takes into account travel time of electric vehicles (EVs) to the station, queuing time and voltage deviation of AC/DC distribution networks is constructed. The dynamic weights combined with binary genetic algorithm are used to solve the model. Further, the Voronoi diagram is used to delineate the CSSIS service area. An optimization model is established to determine the final station site with the objective of minimizing the comprehensive investment cost. The number of chargers is optimized by the queuing theory, and the system bus voltage and CSSIS power balance are used as constraints to determine the station equipment capacity. Finally, the effectiveness of the proposed model and method is verified by examples.
Keywords:AC/DC distribution network  electric vehicle  charging-swapping-storage integrated station  Markov  multi-objective planning
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《电力系统自动化》浏览原始摘要信息
点击此处可从《电力系统自动化》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号