Computational performance analysis for centralized coordinated charging methods of plug-in electric vehicles: From the grid operator perspective

Shang, Yitong1,2; Zheng, Yanchong2; Shao, Ziyun3; Jian, Linni2

2019-11-14

10.1002/2050-7038.12229

International Transactions on Electrical Energy Systems   影响因子和分区

2050-7038

With an ever-increasing number of plug-in electric vehicles (PEVs), there is a fast-growing interest in PEVs' charging impact on the stability and the operating cost of power grid as well as the ecological environment. The centralized coordinated charging method is one of the promising solutions to mitigate such undesired impacts as elevating load peaks, increasing energy losses, and decreasing node voltage. However, the computational complexity is a critical issue to obtain the coordinated charging strategies especially for a large number of PEVs. In this context, it is very essential to analyze the computational performance of the centralized coordinated charging methods. In this paper, a paradigm for analyzing the computational performance is provided. Three centralized methods with different standpoint, viz., to minimize carbon emissions, to minimize load variance, and to minimize generation cost, are investigated to conduct a computational performance analysis from the grid operator perspective. First, the optimization theory is employed to transform the three engineering problems into the mathematical programming models. Then, whether the mathematical programming models are convex or nonconvex is analyzed. The results show that the first two mathematical programming models are convex, and the third mathematical programming model is nonconvex. And it demonstrates that the centralized scheduling model that is convex programming has a better computational performance theoretically. At last, simulations are carried out to verify the theoretical computational performance for different types of centralized coordinated charging methods.

centralized coordinated charging method computational performance convex analysis plug-in electric vehicles

SCI ; EI

英语

通讯

National Natural Science Foundation of China[61773195]

Engineering

Engineering, Electrical & Electronic

WOS:000496407100001

WILEY

20194707717471

Charging (batteries) ; Convex optimization ; Cost benefit analysis ; Electric automobiles ; Electric power system stability ; Electric power transmission networks ; Energy dissipation ; Mathematical transformations ; Site selection ; Vehicle performance ; Vehicle-to-grid

Energy Losses (industrial and residential):525.4 ; Automobiles:662.1 ; Secondary Batteries:702.1.2 ; Electric Power Systems:706.1 ; Electric Power Transmission:706.1.1 ; Cost and Value Engineering; Industrial Economics:911 ; Mathematical Transformations:921.3

Web of Science

1.Harbin Inst Technol, Harbin 150001, Heilongjiang, Peoples R China
2.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen 518055, Peoples R China
3.Guangzhou Univ, Sch Mech & Elect Engn, Guangzhou, Guangdong, Peoples R China

Shang, Yitong,Zheng, Yanchong,Shao, Ziyun,et al. Computational performance analysis for centralized coordinated charging methods of plug-in electric vehicles: From the grid operator perspective[J]. International Transactions on Electrical Energy Systems,2019,30(2).

Shang, Yitong,Zheng, Yanchong,Shao, Ziyun,&Jian, Linni.(2019).Computational performance analysis for centralized coordinated charging methods of plug-in electric vehicles: From the grid operator perspective.International Transactions on Electrical Energy Systems,30(2).

Shang, Yitong,et al."Computational performance analysis for centralized coordinated charging methods of plug-in electric vehicles: From the grid operator perspective".International Transactions on Electrical Energy Systems 30.2(2019).