Kai Deng, Yun Zhang, Zhongwei Chen, Haotian Liu, Peizhe Li, Zheng Lan
{"title":"Optimal Charging Strategy for Electric Vehicles Based on Hybrid Hierarchical Framework","authors":"Kai Deng, Yun Zhang, Zhongwei Chen, Haotian Liu, Peizhe Li, Zheng Lan","doi":"10.1145/3386415.3387040","DOIUrl":null,"url":null,"abstract":"The massive roll-out of electric vehicles burden the electricity grid with stochastic load. It is imperative to address this issue either by expanding and reinvesting the network or regulating the charging load in a smart way. This paper proposed a novel hybrid hierarchical strategy for electric vehicle (EV) charging. By synthesizing the strength of the two mainstream control strategies-centralized and decentralized control strategy, it divides the charging process into two levels with different optimal objectives. Considering the stochastic of the charging behavior, it deploys MATSim to simulate the driving patterns and aggregate the EV with similar driving patterns into a so-called Virtual Battery Aggregation (VBA) Model. To verify the effectiveness of the proposed method, an 18-bus system is simulated and 4 different control methods are compared and analyzed regarding to peak hour node voltage, line load, and daily load curve.","PeriodicalId":250211,"journal":{"name":"Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3386415.3387040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The massive roll-out of electric vehicles burden the electricity grid with stochastic load. It is imperative to address this issue either by expanding and reinvesting the network or regulating the charging load in a smart way. This paper proposed a novel hybrid hierarchical strategy for electric vehicle (EV) charging. By synthesizing the strength of the two mainstream control strategies-centralized and decentralized control strategy, it divides the charging process into two levels with different optimal objectives. Considering the stochastic of the charging behavior, it deploys MATSim to simulate the driving patterns and aggregate the EV with similar driving patterns into a so-called Virtual Battery Aggregation (VBA) Model. To verify the effectiveness of the proposed method, an 18-bus system is simulated and 4 different control methods are compared and analyzed regarding to peak hour node voltage, line load, and daily load curve.