Distributed Online Optimization for Charging and Discharging of Plug-in Electric Vehicles

被引：0
|
作者：
Xiong, Haiming [1 ,2 ]
Chi, Ming [1 ,2 ]
Liu, Zhi-Wei [1 ,2 ]
Hu, Dandan [3 ]
Zhu, Liang -Liang [4 ,5 ]
Jiang, Cheng [4 ,5 ]
Gui, Jun -Ping [4 ,5 ]
Rao, Yao [4 ,5 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Minist Educ, Wuhan 430074, Peoples R China
[3] South Cent Univ National, Sch Management, Wuhan 430074, Peoples R China
[4] Nari Grp Corp State Grid Elect Power Res Inst, Nanjing 210000, Peoples R China
[5] Wuhan Efficiency Evaluat Co Ltd, State Grid Elect Power Res Inst, Wuhan, Peoples R China
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON CYBORG AND BIONIC SYSTEMS, CBS | 2022年
关键词：
ENERGY MANAGEMENT; STRATEGY; STATION; PRICE;
D O I：
10.1109/CBS55922.2023.10115405
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The increasing number of uncoordinated charging and discharging for plug-in electric vehicles (PEVs) poses new challenges to the operation of the distribution network. We introduce a dynamic price mechanism so that charging at peak load will lead to an increase in cost. Then, a distributed online charging and discharging scheduling scheme for PEVs based on the dynamic price mechanism is proposed, considering the minimization of charging cost and battery degradation cost. Unlike most of the existing studies that require the future information of PEVs to schedule charging, the proposed algorithm can solve the scheduling problem for PEVs by taking advantage of a distributed alternating direction method of multipliers (ADMM). Simulation results demonstrate the effectiveness and correctness of the proposed scheduling scheme.
引用
收藏
页码：407 / 412
页数：6
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