基于机会约束规划的含电动汽车市域铁路牵引供电系统优化运行

doi:10.19799/j.cnki.2095-4239.2023.0487

摘要/Abstract

摘要：

市域铁路为市区和郊区提供了便捷通道，沿线车站不仅可实现电动汽车停车换乘，也为电动汽车接入铁路牵引供电系统提供了友好接口。为了提升列车再生制动能量利用率，降低市域铁路运营成本，本文提出了一种含电动汽车的同相牵引供电系统优化运行模型，以牵引变电所日电费成本最低为目标，优化电动汽车和超级电容的充放电策略、牵引变电所功率调控策略。为应对电动汽车到达时间、离开时间和初始荷电状态的不确定性，使用机会约束规划，利用概率约束代替传统确定约束，保证电动汽车充电方案满足驾驶要求的置信水平高于预定的置信水平。使用样本均值法将机会约束转换为确定性约束，得到混合整数线性规划模型，然后采用CPLEX求解器求解。仿真分析表明，提出的模型可以有效降低牵引变电所日电费20.37%，体现出了电动汽车在参与牵引供电系统负荷调节中具有良好的灵活性，有效提高了系统的运行经济性。

关键词: 市域铁路, 储能, 电动汽车, 同相牵引供电系统, 机会约束规划

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

中图分类号:

U 223

唐兆祥, 许万涛, 邓昊, 卢文杰. 基于机会约束规划的含电动汽车市域铁路牵引供电系统优化运行[J]. 储能科学与技术, 2024, 13(2): 526-535.

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.

图/表 12

图1

表1

牵引变电所基本参数"

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

表1

表2

表3

图2

表4

图3

图4

图5

图6

表5

图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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