Charging Scheduling of Electric Vehicles (EV) in Probabilistic Scenario considering Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G)

被引:0
|
作者
Das, Sourav [1 ]
Bhattacharya, Aniruddha [1 ]
Acharjee, Parimal [1 ]
机构
[1] Natl Inst Technol Durgapur, Dept Elect Engn, Durgapur, India
来源
2020 IEEE CALCUTTA CONFERENCE (CALCON) | 2020年
关键词
2m-Point Estimation Method; Charging Management; Electric vehicles; G2V; Non-parametric test; Probability; V2G;
D O I
10.1109/calcon49167.2020.9106552
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper aims a Charging Scheduling Algorithm (CSA) with the intension to minimize the total daily charging cost of electric vehicles present in the parking area of university or any workplace. The uncertainties about each trip distances and daily mileages of EVs are considered and 2m Point Estimation Method (2m-PEM) is used to tackle this stochastic framework. Moreover, in this proposed algorithm both V2G and G2V technology is contemplated simultaneously. Soft computing technique is integrated with this algorithm in order to minimize the complexity of the charging management problem. Two test cases, containing lower battery capacity vehicles and higher battery capacity vehicles are considered and the proposed algorithm is applied. Later, the robustness of the algorithm is verified using Wilcoxon Signed rank test (WSRT).
引用
收藏
页码:467 / 472
页数:6
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