{"title":"消费者前提下降低高峰需求的电动汽车最优充电算法","authors":"Dhanushka S. Lokunarangoda, I. Premaratne","doi":"10.1109/COMPTELIX.2017.8004050","DOIUrl":null,"url":null,"abstract":"A major challenge in the power sector is about to take place since the main Japanese and Asian car manufacturers have announced that all manufactured cars from 2017 will be battery powered. Main effect of increasing the number of Electric Vehicles on power systems is the creation of a significant domestic demand for electricity. Electric vehicles are in the forefront of emerging zero emission technologies that are essential for a sustainable future. Due to the fast growing demand for electric vehicles, it will be a key point to consider when managing the power utilization in Sri Lanka. As peak demand is heavily catered using diesel power, commercial and environmental success relies on concentrating vehicle-charging activities to non-peak hours. An intelligent interface between electricity supply and electric vehicle will help to optimize the electricity demand and reduce the weight at peak demand time. This research worked towards the design and development of a cost effective, high accuracy intelligent socket outlet for charging of electric vehicles to minimize the effect of electric vehicle charging on national grid, hence reduce the environmental and economic impact. For the intelligent determination of charging time, an algorithm has been developed based on historical demand data, existing charge of the battery and the user requirements.","PeriodicalId":6917,"journal":{"name":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","volume":"6 1","pages":"654-658"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimum charging algorithm for electric vehicles to reduce the peak demand in consumer premise\",\"authors\":\"Dhanushka S. Lokunarangoda, I. Premaratne\",\"doi\":\"10.1109/COMPTELIX.2017.8004050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A major challenge in the power sector is about to take place since the main Japanese and Asian car manufacturers have announced that all manufactured cars from 2017 will be battery powered. Main effect of increasing the number of Electric Vehicles on power systems is the creation of a significant domestic demand for electricity. Electric vehicles are in the forefront of emerging zero emission technologies that are essential for a sustainable future. Due to the fast growing demand for electric vehicles, it will be a key point to consider when managing the power utilization in Sri Lanka. As peak demand is heavily catered using diesel power, commercial and environmental success relies on concentrating vehicle-charging activities to non-peak hours. An intelligent interface between electricity supply and electric vehicle will help to optimize the electricity demand and reduce the weight at peak demand time. This research worked towards the design and development of a cost effective, high accuracy intelligent socket outlet for charging of electric vehicles to minimize the effect of electric vehicle charging on national grid, hence reduce the environmental and economic impact. For the intelligent determination of charging time, an algorithm has been developed based on historical demand data, existing charge of the battery and the user requirements.\",\"PeriodicalId\":6917,\"journal\":{\"name\":\"2017 International Conference on Computer, Communications and Electronics (Comptelix)\",\"volume\":\"6 1\",\"pages\":\"654-658\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computer, Communications and Electronics (Comptelix)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPTELIX.2017.8004050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer, Communications and Electronics (Comptelix)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPTELIX.2017.8004050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimum charging algorithm for electric vehicles to reduce the peak demand in consumer premise
A major challenge in the power sector is about to take place since the main Japanese and Asian car manufacturers have announced that all manufactured cars from 2017 will be battery powered. Main effect of increasing the number of Electric Vehicles on power systems is the creation of a significant domestic demand for electricity. Electric vehicles are in the forefront of emerging zero emission technologies that are essential for a sustainable future. Due to the fast growing demand for electric vehicles, it will be a key point to consider when managing the power utilization in Sri Lanka. As peak demand is heavily catered using diesel power, commercial and environmental success relies on concentrating vehicle-charging activities to non-peak hours. An intelligent interface between electricity supply and electric vehicle will help to optimize the electricity demand and reduce the weight at peak demand time. This research worked towards the design and development of a cost effective, high accuracy intelligent socket outlet for charging of electric vehicles to minimize the effect of electric vehicle charging on national grid, hence reduce the environmental and economic impact. For the intelligent determination of charging time, an algorithm has been developed based on historical demand data, existing charge of the battery and the user requirements.