{"title":"基于实时价格的电动汽车多目标控制策略研究","authors":"Tu Yi-yun","doi":"10.1109/ICIEA.2016.7603865","DOIUrl":null,"url":null,"abstract":"This paper establish mathematical models aimed at minimizing the peak-valley difference of power load and maximizing the profit of consumer for the participation of EVs on the base of adopting real-time price in electricity market. Then solve it by Particle Swarm Optimization(PSO) algorithm, obtain load curves between EVs and power grid. Results show that effect of load regulation and value of profit have obvious variation on different weight coefficients, thus realize multi-target control strategy.","PeriodicalId":283114,"journal":{"name":"2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The research on multi-target control strategy of EVs based on real-time price\",\"authors\":\"Tu Yi-yun\",\"doi\":\"10.1109/ICIEA.2016.7603865\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper establish mathematical models aimed at minimizing the peak-valley difference of power load and maximizing the profit of consumer for the participation of EVs on the base of adopting real-time price in electricity market. Then solve it by Particle Swarm Optimization(PSO) algorithm, obtain load curves between EVs and power grid. Results show that effect of load regulation and value of profit have obvious variation on different weight coefficients, thus realize multi-target control strategy.\",\"PeriodicalId\":283114,\"journal\":{\"name\":\"2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIEA.2016.7603865\",\"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 11th Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2016.7603865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The research on multi-target control strategy of EVs based on real-time price
This paper establish mathematical models aimed at minimizing the peak-valley difference of power load and maximizing the profit of consumer for the participation of EVs on the base of adopting real-time price in electricity market. Then solve it by Particle Swarm Optimization(PSO) algorithm, obtain load curves between EVs and power grid. Results show that effect of load regulation and value of profit have obvious variation on different weight coefficients, thus realize multi-target control strategy.
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