Md. Navid Bin Anwar, Rukhsana Ruby, Yijun Cheng, Jianping Pan
{"title":"Time-of-Use-Aware Priority-Based Multi-Mode Online Charging Scheme for EV Charging Stations","authors":"Md. Navid Bin Anwar, Rukhsana Ruby, Yijun Cheng, Jianping Pan","doi":"10.1109/SmartGridComm52983.2022.9961019","DOIUrl":null,"url":null,"abstract":"Electric vehicle charging stations (EVCS) play a vital role in providing charging support to EV users. In order to facilitate users in terms of charging speed, two different charging modes (L2 and L3) are currently available at public charging stations. L3 mode provides quick charging with higher power, whereas L2 mode offers moderate charging speed with low power. The integration of an EVCS into the power grid requires coordinated charging strategies in order to reduce the electricity bill for a profitable operation. However, the effective utilization of the multi-mode charging strategy to serve the maximum number of EVs for a small charging station with limited charging capacity and spots is an open issue. To this end, we propose a priority-based online charging scheme, namely PBOS, which is based on real-time information and does not depend on future knowledge. The objective is to serve as many vehicles as possible in a day while fulfilling their charging requirements under a multi-mode EVCS setting and reducing the charging costs by utilizing the time-of-use pricing based demand response strategy. Simulation results show that the proposed algorithm can increase profit for EVCS by up to 42% with a 20% lower rejection rate when compared with other schemes.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartGridComm52983.2022.9961019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Electric vehicle charging stations (EVCS) play a vital role in providing charging support to EV users. In order to facilitate users in terms of charging speed, two different charging modes (L2 and L3) are currently available at public charging stations. L3 mode provides quick charging with higher power, whereas L2 mode offers moderate charging speed with low power. The integration of an EVCS into the power grid requires coordinated charging strategies in order to reduce the electricity bill for a profitable operation. However, the effective utilization of the multi-mode charging strategy to serve the maximum number of EVs for a small charging station with limited charging capacity and spots is an open issue. To this end, we propose a priority-based online charging scheme, namely PBOS, which is based on real-time information and does not depend on future knowledge. The objective is to serve as many vehicles as possible in a day while fulfilling their charging requirements under a multi-mode EVCS setting and reducing the charging costs by utilizing the time-of-use pricing based demand response strategy. Simulation results show that the proposed algorithm can increase profit for EVCS by up to 42% with a 20% lower rejection rate when compared with other schemes.