Placement of electric vehicle fast charging stations in distribution network considering power loss, land cost, and electric vehicle population

被引:27
|
作者
Ahmad, Fareed [1 ]
Iqbal, Atif [2 ]
Ashraf, Imtiaz [1 ]
Marzband, Mousa [3 ]
Khan, Irfan [4 ]
机构
[1] Aligarh Muslim Univ, Dept Elect Engn, Aligarh 202002, Uttar Pradesh, India
[2] Qatar Univ, Dept Elect Engn, Doha, Qatar
[3] Northumbria Univ, Dept Math Phys & Elect Engn, Newcastle Upon Tyne, Tyne & Wear, England
[4] Texas A&M Univ, Clean & Resilient Energy Syst Cares Lab, Galveston, TX USA
关键词
Fast-charging stations; electric vehicle population; land cost index; gray wolf optimization; optimal placement; ALLOCATION; OPTIMIZATION; ALGORITHM; PSO;
D O I
10.1080/15567036.2022.2055233
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
Recently, electric vehicles (EVs) gained tremendous attention from government agencies and the automotive industry due to lower CO2 emissions, low maintenance, and operating costs. However, due to increasing EV penetration, the EV's load affects the distribution network parameters like power loss, voltage profile, and harmonic distortion. Therefore, the proper placement of EV fast-charging stations (FCSs) is required for the reliability of the distribution network. Further, this paper proposes two-stage processes for the placement of FCSs. In the first stage, the charging station owner decision index (CSODI) has been introduced considering the land cost index (LCI) and electric vehicle flow index (EVFI). The CSODI has been formulated to minimize the land cost and maximize the EVs flow for FCSs placement. In the next stage, an optimization problem is formulated for minimizing the total active power loss by considering the distribution system operator (DSO) constraints. In addition, the minimization problem has been solved using the hybrid gray wolf optimization-particle swarm optimization (GWOPSO) algorithm. Therefore, the best possible locations were obtained by the GWOPSO with 198.93 kW power loss. Furthermore, the average 2.02% power loss for the GWOPSO technique is lower when compared to the PSO technique.
引用
收藏
页码:1693 / 1709
页数:17
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