极端天气下高速公路自洽能源系统移动电源车的优化调度

doi:10.13229/j.cnki.jdxbgxb.20240224

吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (11): 3623-3631.doi: 10.13229/j.cnki.jdxbgxb.20240224

• 交通运输工程·土木工程 • 上一篇

极端天气下高速公路自洽能源系统移动电源车的优化调度

李艳波¹(),刘妙阳²,杨凯³,张云锐¹,吕浩楠¹,王秋才²()

^1.长安大学能源与电气工程学院，西安 710064
^2.长安大学电子与控制工程学院，西安 710064
^3.山东省交通规划设计院集团有限公司，济南 250101

收稿日期:2024-03-06 出版日期:2025-11-01 发布日期:2026-02-03
通讯作者: 王秋才 E-mail:ybl@chd.edu.cn;qcwang@chd.edu.cn
作者简介:李艳波（1980-），男，副教授，博士.研究方向：交通能源融合，智能微电网.E-mail：ybl@chd.edu.cn
基金资助:
国家重点研发计划项目(2021YFB1600202);河南交通投资集团有限公司科技项目(HNJT2024-18);河南交通投资集团有限公司科技项目(HNJT2024-35)

Optimal scheduling of mobile power vehicles for highway self-consistent energy systems in extreme weather conditions

Yan-bo LI¹(),Miao-yang LIU²,Kai YANG³,Yun-rui ZHANG¹,Hao-nan LYU¹,Qiu-cai WANG²()

^1.School of Energy and Electrical Engineering，Chang'an University，Xi'an 710064 China
^2.School of Electronic and Control Engineering，Chang'an University，Xi'an 710064，China
^3.Shandong Traffic Planning Design Institute Group Co. ，Ltd. ，Jinan 250101，China

Received:2024-03-06 Online:2025-11-01 Published:2026-02-03
Contact: Qiu-cai WANG E-mail:ybl@chd.edu.cn;qcwang@chd.edu.cn

摘要/Abstract

摘要：

近年来，极端天气对高速公路电网系统造成严重破坏，如何合理调配移动电源车是目前高速公路故障抢修中亟须解决的难题。因此，本文提出了一种极端天气下高速公路移动电源车的优化调度方法。首先，利用蒙特卡洛模拟方法，通过历史天气数据和实际线路参数，构建极端天气下覆冰载荷、风力载荷和绝缘子闪络的数学模型，得到输电线路脆弱性模型，进而确定整个系统的故障情况；其次，通过蒙特卡洛模拟方法和目标函数收敛条件，求出移动电源车的最优接入点，调度移动电源车提高系统弹性；最后，利用新疆某高速公路服务区自洽能源系统数据进行仿真分析。结果表明，相比于目前常用的移动电源车接入点固定不变的方法，本文提出的调度方法使恢复供电的负荷比例提高了12%，提升了移动电源车的工作效率和自洽能源系统的弹性性能。

关键词: 高速公路, 自洽能源系统, 极端天气, 移动电源车调度, 蒙特卡洛模拟, 弹性提高

Abstract:

Extreme weather in recent years has caused serious damage to the highway power grid system， how to reasonably deploy mobile power vehicles is the current highway fault repair in the urgent need to solve the problem. Therefore， this paper proposes an optimal scheduling method for mobile power vehicles on highways under extreme weather. Firstly， the Monte Carlo simulation method is used to construct mathematical models of ice-covering load， wind load and insulator flashover under extreme weather through historical weather data and actual line parameters， to obtain the vulnerability model of the transmission line， and then to determine the fault conditions in the whole system. Secondly， the Monte Carlo simulation method and the convergence condition of the objective function are used to find out the optimal access point of the mobile power vehicle， and the mobile power vehicle is dispatched to improve the system resilience. Finally， the simulation analysis is carried out by using the data of the self-consistent energy system of a highway service area in Xinjiang. The results show that compared with the commonly used method of fixing the access point of mobile power vehicles， the dispatching method proposed in this paper increases the proportion of loads that are restored to the power supply by 12%， which enhances the efficiency of mobile power vehicle and the resilience performance of the self-consistent energy system.

Key words: highway, self-consistent energy system, extreme weather, mobile power vehicle scheduling, Monte Carlo simulation, resilience improvement

中图分类号:

U491.8

李艳波,刘妙阳,杨凯,张云锐,吕浩楠,王秋才. 极端天气下高速公路自洽能源系统移动电源车的优化调度[J]. 吉林大学学报(工学版), 2025, 55(11): 3623-3631.

Yan-bo LI,Miao-yang LIU,Kai YANG,Yun-rui ZHANG,Hao-nan LYU,Qiu-cai WANG. Optimal scheduling of mobile power vehicles for highway self-consistent energy systems in extreme weather conditions[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(11): 3623-3631.

图/表 11

图1

图2

图3

表1

线路实际距离长度及通行时间"

路段	距离长度/ km	理论通行时间/min	参数 $K$ 和 $D$	实际通行时间/min
1.1-1.2	13.3	8	0.5×0.6	13.3
1.2-1.3	15	9		15
1.3-1.4	15	9		15
1.4-1.5	16.7	10		16.7
2.1-2.2	21.7	13		21.7
2.2-2.3	18.3	11		18.3
2.3-2.4	18.3	11		18.3
3.1-3.2	15	9		15
3.2-3.3	15	9		15

表1

表2

表3

图4

表4

微电网弹性评估指标"

弹性指标	$M A D T M / h$	$M A T P M / h$	$M E R C M$	$M A T C M / h$	$M E C E M$
数值	3.09	2.25	0.626 8	4.27	4.646 0

表4

图5

图6

表5

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仿真	A-B		A-C		B-C		B-D		C-D
仿真	时间/ h	路段	时间/ h	路段	时间/ h	路段	时间/ h	路段	时间/ h	路段
1	—	—	2.20	2.3	—	—	4.54	4.1	—	—
2	3.56	1.3	3.13	2.2	—	—	—	—	4.34	5.1
3	3.31	1.2	4.19	2.3	—	—	4.97	4.2	5.18	5.2
4	1.61	1.4	2.83	2.1	3.91	3.3	4.46	4.1	5.26	5.2
5	3.90	1.4	—	—	4.30	3.3	—	—	4.96	5.1
6	1.62	1.3	2.73	2.1	—	—	4.27	4.1	—	—
7	—	—	3.31	2.2	3.83	3.3	—	—	4.74	5.2
8	2.95	1.4	3.25	2.3	—	—	4.38	4.1	4.52	5.2

路段	故障概率	路段	故障概率
1.1-1.2	0.236 3	2.3-2.4	0.194 7
1.2-1.3	0.217 6	3.1-3.2	0.148 2
1.3-1.4	0.191 3	3.2-3.3	0.139 7
1.4-1.5	0.169 1	4.1-4.2	0.141 5
2.1-2.2	0.221 3	5.1-5.2	0.167 3
2.2-2.3	0.207 4

极端天气下高速公路自洽能源系统移动电源车的优化调度

Optimal scheduling of mobile power vehicles for highway self-consistent energy systems in extreme weather conditions

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