Aggregator Analysis for Efficient Day-Time Charging of Plug-in Hybrid Electric Vehicles

被引:0
|
作者
Bandyopadhyay, Anik [1 ]
Wang, Lingfeng [1 ]
Devabhaktuni, Vijay K. [1 ]
Green, Robert C., II [1 ]
机构
[1] Univ Toledo, Dept EECS, Toledo, OH 43606 USA
关键词
PHEVs; V2G; aggregator; Li-ion Battery; binary particle swarm optimization (BPSO);
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The introduction of Plug-in Hybrid Electric Vehicles (PHEVs) will result in the synergy of the transportation sector and the electric power sector. The widespread use of PHEVs over the next few years will result in a great number of benefits to the electric power sector as well as have significant environmental benefits. Utilizing Vehicle to Grid (V2G) technology, the PHEV will be able to feed power into the grid. The V2G feature will also enable the PHEV user to earn revenue. However, multiple V2G transactions between vehicle and grid could result in battery degradation. Smart aggregator action coupled with a thorough understanding of battery models is the key to ensuring that a balance is obtained between the need for profit and ensuring the proper maintenance of battery health parameters. In this paper the optimal charging profile is calculated using Binary Particle Swarm Optimization (BPSO). The charge trajectory of the Li-ion battery is analyzed with respect to the number of V2G transactions that take place between 9 AM to 5 PM.
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页数:8
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