{"title":"基于二元分解的电动汽车最优调度","authors":"Jinfeng Yang, Zaiyue Yang","doi":"10.1109/CCDC.2014.6852522","DOIUrl":null,"url":null,"abstract":"This paper concentrates on the optimal scheduling of electric vehicle (EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then, a modified online approach is introduced to alleviate the impact of price prediction error. The simulation reveals that our algorithms can reduce the cost to a large extent. Furthermore, it is demonstrated that the online scheduling scheme can achieve a similar performance compared with the optimal scheduling scheme having full knowledge of real time prices (RTP).","PeriodicalId":380818,"journal":{"name":"The 26th Chinese Control and Decision Conference (2014 CCDC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimal scheduling of electric vehicle using dual decomposition\",\"authors\":\"Jinfeng Yang, Zaiyue Yang\",\"doi\":\"10.1109/CCDC.2014.6852522\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper concentrates on the optimal scheduling of electric vehicle (EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then, a modified online approach is introduced to alleviate the impact of price prediction error. The simulation reveals that our algorithms can reduce the cost to a large extent. Furthermore, it is demonstrated that the online scheduling scheme can achieve a similar performance compared with the optimal scheduling scheme having full knowledge of real time prices (RTP).\",\"PeriodicalId\":380818,\"journal\":{\"name\":\"The 26th Chinese Control and Decision Conference (2014 CCDC)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 26th Chinese Control and Decision Conference (2014 CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2014.6852522\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 26th Chinese Control and Decision Conference (2014 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2014.6852522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal scheduling of electric vehicle using dual decomposition
This paper concentrates on the optimal scheduling of electric vehicle (EV). The EV is scheduled for both operating stage and non-operating stage. With full consideration of operating income, regulation revenue and the owner's habit, the cost minimization problem is formulated as a convex programming with coupling constrains. Dual decomposition is utilized to obtain the global optimal solution. Then, a modified online approach is introduced to alleviate the impact of price prediction error. The simulation reveals that our algorithms can reduce the cost to a large extent. Furthermore, it is demonstrated that the online scheduling scheme can achieve a similar performance compared with the optimal scheduling scheme having full knowledge of real time prices (RTP).