Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (8): 2238-2244.doi: 10.13229/j.cnki.jdxbgxb.20221364

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Double layer optimization model of charging pile based on random charging demand

Yun-juan YAN1(),Wei-xiong ZHA2(),Jun-gang SHI2,Li-ping YAN3   

  1. 1.College of Mechatronics & Vehicle Engineering,East China Jiaotong University,Nanchang 330013,China
    2.Institute of Transportation and Economics,East China Jiaotong University,Nanchang 330013,China
    3.School of Software,East China Jiaotong University,Nanchang 330013,China
  • Received:2022-10-25 Online:2024-08-01 Published:2024-08-30
  • Contact: Wei-xiong ZHA E-mail:xiaoyan921@sohu.com;jxzhawx@sina.com

Abstract:

In the mixed transportation network with random charging demand, a bi-level programming model is built to determine the reasonable number of charging piles. The upper model aims to minimize the sum of the net present value of the construction cost, the cost of customer loss, and the cost of exceeding the endurance time; the lower level model aims to minimize the user's generalized travel cost to describe the interaction between the road network flow allocation and the location of charging facilities. The model uses differential evolution algorithm and Frank-Wolfe algorithm nested to carry out traffic equilibrium assignment and charging pile configuration optimization simulation. The results show that the model can effectively simulate and predict network equilibrium traffic flow, random charging flow, queuing loss rate and optimal number of charging piles.

Key words: transportation planning and management, bi-level programming model, Frank-Wolfe algorithm, differential evolution algorithm, charging pile configuration

CLC Number: 

  • U491

Fig.1

Sioux-Falls traffic network diagram"

Table 1

Modeling parameters"

参数参数参数
Cu,fi6.2万元Cg2.67元/kmμ10.64
Cs2.76万元/桩Ce0.216元/kmμ20.35
CTlost50元/hwmax30 minα10.5
CBlost0.25元/(辆?h)Cu,oheri640元/(年?车位)α20.3
βg0.6min/元βe0.6 min/元σ10.12
l10年ωaverage0.36度/hσ20.08
ir0.1H1000ρmin0.6
Ns200CR0.01F0.4
Su100h0.0001Ms50

Fig.2

SOC probability density distribution"

Table 2

Optimal configuration parameters of alternative charging stations"

配置参数最优结果
备选充电站位置511151624
最优充电桩配置数/个638810010068
系统容量/个95132150150102
均衡充电流量/(辆?h-14745846851014520
平均逗留时间/h0.1360.1260.1260.1830.139
平均队长/(辆?h-165748614677
损失率0.0052.68e-065.71e-060.210.007

Fig.3

Link equilibrium flow"

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