Hengjie Li, L. Wen, Wei Chen, Xu Gong, Xianqiang Zeng
{"title":"私人电动汽车快速协调充电策略","authors":"Hengjie Li, L. Wen, Wei Chen, Xu Gong, Xianqiang Zeng","doi":"10.1109/IAEAC.2018.8577842","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of the rapid and coordinated charging of private electric vehicles, two coordinated charging strategies were formulated under the rapid charging mode. One is to establish a coordinated charging strategy that minimizes the total charging time of electric vehicles, the minimum of power standard deviation and the peak-valley difference of distribution networks. The multi-objective function is normalized to a single-target solution by weighted summation method. The other is to use the total charging time of electric vehicles as a constraint to achieve peak clipping and filling of the distribution network. Taking the collected traffic data of weekdays and holidays in Lanzhou City as an example, two kinds of coordinated optimization schemes were simulated and analyzed on weekdays and holidays conditions respectively, and the genetic algorithm was used to solve the problem. The results show that the total charging time is the smallest when charging is uncoordinated charging, and peak clipping and filling effect of the distribution network is the worst; when electric vehicles do not consider the time target for coordinated charging, peak clipping and filling effect of the distribution network is the best and the total charging time is the longest; when electric vehicles contain the time target for coordinated charging, peak clipping and filling effect of the distribution network is intermediate.","PeriodicalId":6573,"journal":{"name":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"44 1","pages":"196-200"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Rapid and Coordinated Charging Strategy for Private Electric Vehicles\",\"authors\":\"Hengjie Li, L. Wen, Wei Chen, Xu Gong, Xianqiang Zeng\",\"doi\":\"10.1109/IAEAC.2018.8577842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem of the rapid and coordinated charging of private electric vehicles, two coordinated charging strategies were formulated under the rapid charging mode. One is to establish a coordinated charging strategy that minimizes the total charging time of electric vehicles, the minimum of power standard deviation and the peak-valley difference of distribution networks. The multi-objective function is normalized to a single-target solution by weighted summation method. The other is to use the total charging time of electric vehicles as a constraint to achieve peak clipping and filling of the distribution network. Taking the collected traffic data of weekdays and holidays in Lanzhou City as an example, two kinds of coordinated optimization schemes were simulated and analyzed on weekdays and holidays conditions respectively, and the genetic algorithm was used to solve the problem. The results show that the total charging time is the smallest when charging is uncoordinated charging, and peak clipping and filling effect of the distribution network is the worst; when electric vehicles do not consider the time target for coordinated charging, peak clipping and filling effect of the distribution network is the best and the total charging time is the longest; when electric vehicles contain the time target for coordinated charging, peak clipping and filling effect of the distribution network is intermediate.\",\"PeriodicalId\":6573,\"journal\":{\"name\":\"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"volume\":\"44 1\",\"pages\":\"196-200\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAEAC.2018.8577842\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC.2018.8577842","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Rapid and Coordinated Charging Strategy for Private Electric Vehicles
In order to solve the problem of the rapid and coordinated charging of private electric vehicles, two coordinated charging strategies were formulated under the rapid charging mode. One is to establish a coordinated charging strategy that minimizes the total charging time of electric vehicles, the minimum of power standard deviation and the peak-valley difference of distribution networks. The multi-objective function is normalized to a single-target solution by weighted summation method. The other is to use the total charging time of electric vehicles as a constraint to achieve peak clipping and filling of the distribution network. Taking the collected traffic data of weekdays and holidays in Lanzhou City as an example, two kinds of coordinated optimization schemes were simulated and analyzed on weekdays and holidays conditions respectively, and the genetic algorithm was used to solve the problem. The results show that the total charging time is the smallest when charging is uncoordinated charging, and peak clipping and filling effect of the distribution network is the worst; when electric vehicles do not consider the time target for coordinated charging, peak clipping and filling effect of the distribution network is the best and the total charging time is the longest; when electric vehicles contain the time target for coordinated charging, peak clipping and filling effect of the distribution network is intermediate.