{"title":"Optimization of Electric Vehicle Charging to Shave Peak Load for Integration in Smart Grid","authors":"Bidya Debnath, S. Biswas, M. Uddin","doi":"10.1109/TENSYMP50017.2020.9231029","DOIUrl":null,"url":null,"abstract":"Current movement towards electric vehicle (EV) usage will demand high power consumption in future due to EV charging. As the usage will grow, sudden spike in load curve at busy hours will be a severe problem. This paper focuses on the optimized charging scheduling for EVs to shave peak load for their integration in smart grid. A two layer optimization method is proposed based on the location, charging status of the EV and load scenario of the substations to shave electric peak load. Optimization problem is formulated for each of the layer. The optimization problem of the first layer determines the allowable load level in each hour of a day for each charging station by reducing the peak load of substation. For a new EV, the charging station selection method is proposed by using the allowable peak loads obtained from first layer optimization problem. The optimization problem of the second layer provides an optimized on-off keying charging scheme of the ports for the selected charging stations. The first optimization problem is an off-line root mean square type non-linear problem and the second problem is a binary linear programming. Both the problems are solved for several scenarios by using MATLAB optimization toolboxes. The numerical results show that a significant amount peak load shaving can be achieved by using the proposed method and the percentage of peak load reduction increases with increasing the EV penetration.","PeriodicalId":6721,"journal":{"name":"2020 IEEE Region 10 Symposium (TENSYMP)","volume":"28 1","pages":"483-488"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Region 10 Symposium (TENSYMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENSYMP50017.2020.9231029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Current movement towards electric vehicle (EV) usage will demand high power consumption in future due to EV charging. As the usage will grow, sudden spike in load curve at busy hours will be a severe problem. This paper focuses on the optimized charging scheduling for EVs to shave peak load for their integration in smart grid. A two layer optimization method is proposed based on the location, charging status of the EV and load scenario of the substations to shave electric peak load. Optimization problem is formulated for each of the layer. The optimization problem of the first layer determines the allowable load level in each hour of a day for each charging station by reducing the peak load of substation. For a new EV, the charging station selection method is proposed by using the allowable peak loads obtained from first layer optimization problem. The optimization problem of the second layer provides an optimized on-off keying charging scheme of the ports for the selected charging stations. The first optimization problem is an off-line root mean square type non-linear problem and the second problem is a binary linear programming. Both the problems are solved for several scenarios by using MATLAB optimization toolboxes. The numerical results show that a significant amount peak load shaving can be achieved by using the proposed method and the percentage of peak load reduction increases with increasing the EV penetration.