Optimal operation of urban railway traction power supply system with electric vehicles based on chance-constrained programming

doi:10.19799/j.cnki.2095-4239.2023.0487

Abstract

Abstract:

The urban railway system provides convenient access to urban and suburban areas. The stations along the railway lines offer parking facilities for electric vehicles (EVs) with park-and-ride scheme and serve as a convenient interface for EVs to connect with the railway traction power system. To improve the utilization rate of regenerative braking energy in trains and reduce the operating cost of urban railways, this study proposes an optimal operation model for co-phase traction power substations in conjunction with EVs in urban rail. The primary objective of this model is to minimize the daily electricity cost of the traction substation (TS) by optimizing the charging and discharging strategy of EVs and ultracapacitors, as well as the power regulation strategy of the TS. To address the uncertainties associated with EV arrival time, departure time, and initial charge state, chance-constrained programming ensures that the EV charging scheme meets the driving requirements at a higher confidence level using probabilistic constraints than the predetermined confidence level of traditional deterministic constraints. The model is formulated as a mixed integer linear programming model by converting chance constraints into deterministic constraints using sample average approximation, and the model is subsequently solved using the CPLEX solver. Simulation analysis shows that the proposed model can effectively reduce the daily electricity cost of the TS by 20.37%, which reflects the feasibility of EVs in participating in the load regulation of the traction power supply system, thereby effectively improving the operating economy of the system.

Key words: urban rail, energy storage, electric vehicle, co-phase traction power supply system, chance-constrained programming

CLC Number:

U 223

Zhaoxiang TANG, Wantao XU, Hao DENG, Wenjie LU. Optimal operation of urban railway traction power supply system with electric vehicles based on chance-constrained programming[J]. Energy Storage Science and Technology, 2024, 13(2): 526-535.

Figures/Tables 12

Fig. 1

Table 1

Basic parameters of traction substation"

电网侧

牵引变压器

PFC变流器

U_s

/kV

S_cap

/MVA

ε U ¯

N₁

N₂

U^T

/kV

U^α

/kV

U^β

/kV

S^α

/MVA

S^β

/MVA

110

750

23

27.5

Table 1

Table 2

Table 3

Fig. 2

Table 4

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Table 5

Fig. 7

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参数	时间段	电度电价/(¥/kWh)	售电电价/(¥/kWh)	需量电价/(¥/kW/月)
峰时	8—11, 18—21时	1.252	1.002	42
平时	7 h, 12—17 时	0.782	0.626	42
谷时	0—6 时, 22—0 时	0.370	0.296	42

参数	概率分布类型	A类电动汽车	B类电动汽车
到达时间	正态分布	(μ=480, σ=120)	(μ=1080, σ=120)
离开时间	正态分布	(μ=1080, σ=120)	(μ=480, σ=120)
初始荷电状态/%	正态分布	(μ=40, σ=10)	(μ=40, σ=10)
预期荷电状态/%	均匀分布	(85, 90)	(85, 90)

主要技术指标	电动汽车电池	超级电容
额定容量/kWh	47.3	200
最大功率/kW	50	3000
充放电效率/%	90	95
荷电状态限值/%	[20, 95]	[5, 95]

项目	总电费/万元	电度电费/万元	需量电费/万元	售电收入/万元	总降费比/%
优化前	9.123	7.816	1.307	0	—
优化后	7.265	7.156	0.758	0.649	20.37

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