{"title":"共享电池站的协同优化调度","authors":"Jie Yang, Weiqiang Wang, K. Ma","doi":"10.1109/ICCA.2019.8900011","DOIUrl":null,"url":null,"abstract":"The increasing demand for refueling electrical vehicles (EVs) poses a huge challenge to the stability of power system and the popularity of EVs. While the Battery Swapping Station (BSS) and Battery Charging Station (BCS) provide new fueling methods for electric vehicle users. In this paper, an Aggregative Shared Battery Station (ASBS) model is proposed. In order to solve the problem of large-scale battery supply, a cooperative and optimal dispatching strategy is designed with K-means clustering algorithm. Based on divisional control method, an optimization objective function that considers the maximizing net revenue is established to optimize the number of batteries in each segment in each time slot. The proposed dispatching strategy and objective function are executed with time-of-use tariffs, and the results show that the proposed dispatching strategy and objective function are effective for Shared Battery Station (SBS) scheduling to meet the customer’s battery requirements, and ensure the SBS sustainable and safety operation.","PeriodicalId":130891,"journal":{"name":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","volume":" 12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative and Optimal Dispatch for Shared Battery Stations\",\"authors\":\"Jie Yang, Weiqiang Wang, K. Ma\",\"doi\":\"10.1109/ICCA.2019.8900011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing demand for refueling electrical vehicles (EVs) poses a huge challenge to the stability of power system and the popularity of EVs. While the Battery Swapping Station (BSS) and Battery Charging Station (BCS) provide new fueling methods for electric vehicle users. In this paper, an Aggregative Shared Battery Station (ASBS) model is proposed. In order to solve the problem of large-scale battery supply, a cooperative and optimal dispatching strategy is designed with K-means clustering algorithm. Based on divisional control method, an optimization objective function that considers the maximizing net revenue is established to optimize the number of batteries in each segment in each time slot. The proposed dispatching strategy and objective function are executed with time-of-use tariffs, and the results show that the proposed dispatching strategy and objective function are effective for Shared Battery Station (SBS) scheduling to meet the customer’s battery requirements, and ensure the SBS sustainable and safety operation.\",\"PeriodicalId\":130891,\"journal\":{\"name\":\"2019 IEEE 15th International Conference on Control and Automation (ICCA)\",\"volume\":\" 12\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 15th International Conference on Control and Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2019.8900011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Conference on Control and Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2019.8900011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cooperative and Optimal Dispatch for Shared Battery Stations
The increasing demand for refueling electrical vehicles (EVs) poses a huge challenge to the stability of power system and the popularity of EVs. While the Battery Swapping Station (BSS) and Battery Charging Station (BCS) provide new fueling methods for electric vehicle users. In this paper, an Aggregative Shared Battery Station (ASBS) model is proposed. In order to solve the problem of large-scale battery supply, a cooperative and optimal dispatching strategy is designed with K-means clustering algorithm. Based on divisional control method, an optimization objective function that considers the maximizing net revenue is established to optimize the number of batteries in each segment in each time slot. The proposed dispatching strategy and objective function are executed with time-of-use tariffs, and the results show that the proposed dispatching strategy and objective function are effective for Shared Battery Station (SBS) scheduling to meet the customer’s battery requirements, and ensure the SBS sustainable and safety operation.