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

Abstract

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

CLC Number:

U491.8

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.

Figures/Tables 11

Fig.1

Fig.2

Fig.3

Table 1

Actual distance length and travelling time of the line"

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

Table 1

Table 2

Table 3

Fig.4

Table 4

Microgrid resilience assessment index"

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

Table 4

Fig.5

Fig.6

Table 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

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

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