Dynamic Joint Allocation of EV Charging Stations and DGs in Spatio-Temporal Expanding Grids

被引:15
作者
Atat, Rachad [1 ]
Ismail, Muhammad [2 ]
Serpedin, Erchin [3 ]
Overbye, Thomas [3 ]
机构
[1] Texas A&M Univ Qatar, Dept Elect & Comp Engn, Doha, Qatar
[2] Tennessee Technol Univ, Dept Comp Sci, Cookeville, TN 38501 USA
[3] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
关键词
Charging stations allocation; dynamic program; electric vehicles; expanding power grid; and stochastic geometry modeling; NETWORKS;
D O I
10.1109/ACCESS.2019.2963860
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The number of electric vehicles (EVs) and the size of smart grid are witnessing rapid expansion in both spatial and temporal dimensions. This requires an efficient dynamic spatio-temporal allocation strategy of charging stations (CSs). Such an allocation strategy should provide acceptable charging services at different deployment stages while meeting financial and technical constraints. As new CSs get allocated, distributed generation (DG) units need to be also dynamically allocated in both space and time to compensate for the increment in the loads due to the EV charging requests. Unfortunately, existing power grid models are not suitable to reflect such spatio-temporal evolution, and hence, new models need to be developed. In this paper, we propose a spatio-temporal expanding power grid model based on stochastic geometry. Using this flexible model, we perform a dynamic joint allocation of EV CSs and DG units based on a constrained Markov decision process. The proposed dynamic allocation strategy accounts for charging coordination mechanism within each CS, which in turn allows for maximal usage of deployed chargers. We validate the proposed stochastic geometry-based power grid model against IEEE 123-bus test system. Then, we present a case study for a 5-year CSs deployment plan.
引用
收藏
页码:7280 / 7294
页数:15
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