{"title":"海报:电动汽车与远程可再生能源同步充电","authors":"Tobias Kleinschmidt, Oliver Fuhr, C. Wietfeld","doi":"10.1109/VNC.2016.7835983","DOIUrl":null,"url":null,"abstract":"Enabling prosumers to charge their own produced energy at arbitrary locations is a new concept currently being researched. Unfortunately, this concept requires intensive communication between the feed-in system and the electric vehicle (EV). In previous publications, we showed that fluctuation-sensitive model predictive communication is able to reduce the amount of communication necessary by up to 68.2 % while introducing a mean error of 4.11 %. In this poster, we introduce techniques, which reduce the mean error for our system under test to 0.812 %.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Poster: Synchronised charging of electric vehicles with distant renewable energy resources\",\"authors\":\"Tobias Kleinschmidt, Oliver Fuhr, C. Wietfeld\",\"doi\":\"10.1109/VNC.2016.7835983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Enabling prosumers to charge their own produced energy at arbitrary locations is a new concept currently being researched. Unfortunately, this concept requires intensive communication between the feed-in system and the electric vehicle (EV). In previous publications, we showed that fluctuation-sensitive model predictive communication is able to reduce the amount of communication necessary by up to 68.2 % while introducing a mean error of 4.11 %. In this poster, we introduce techniques, which reduce the mean error for our system under test to 0.812 %.\",\"PeriodicalId\":352428,\"journal\":{\"name\":\"2016 IEEE Vehicular Networking Conference (VNC)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Vehicular Networking Conference (VNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VNC.2016.7835983\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Vehicular Networking Conference (VNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VNC.2016.7835983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Poster: Synchronised charging of electric vehicles with distant renewable energy resources
Enabling prosumers to charge their own produced energy at arbitrary locations is a new concept currently being researched. Unfortunately, this concept requires intensive communication between the feed-in system and the electric vehicle (EV). In previous publications, we showed that fluctuation-sensitive model predictive communication is able to reduce the amount of communication necessary by up to 68.2 % while introducing a mean error of 4.11 %. In this poster, we introduce techniques, which reduce the mean error for our system under test to 0.812 %.
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