Multiple-time-section Optimization Strategy for Post-disaster Recovery of Distribution Network Considering Dynamic Changes of Traffic Flow

被引：0

作者：

Wan H. ^{[1
]}

Liu W. ^{[1
]}

Shi Q. ^{[1
]}

He J. ^{[2
]}

Sun W. ^{[2
]}

Zhang X. ^{[2
]}

机构：

[1] School of Electrical and Electronic Engineering, North China Electric Power University, Beijing

[2] China Electric Power Research Institute, Beijing

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 12期

关键词：

Dynamic reconfiguration; Fault recovery; Mobile energy storage; Power grid; Resilience; Traffic flow; Transportation network;

D O I：

10.7500/AEPS20211231008

中图分类号：

学科分类号：

摘要：

Aiming at the influence of the dynamic change characteristics of traffic flow on the fault recovery process of distribution network under extreme disasters, in the background of the coupling of the power grid and transportation network, considering the coordination and scheduling between mobile and fixed emergency recovery resources and fault repair, a multi-time-section optimization strategy for the post-disaster fault recovery of the distribution network is proposed. Firstly, the cell transmission model is used to establish the transportation network model, which can predict the traveling time of the road repair crews and mobile energy storage vehicles. Secondly, a mixed-integer linear programming model is established, which aims at minimizing the load reduction amount and the scheduling cost of restoration resources, and takes the emergency repair sequence of faulty equipment and the scheduling plan of restoration resources as decision variables. The multi-time-section optimization method is used to solve the model. In addition, a method for dynamic reconfiguration of grids is proposed. By adding a virtual root node to form a virtual island with each power loss node, and dynamically adding and deleting the number of nodes in the island with the change of the grid, it is ensured that the entire distribution network can always meet the radial constraints, and the adaptability of the algorithm to fault scenarios is improved. Finally, examples are used to verify the effectiveness of the proposed method in improving the resilience of the distribution network. © 2022 Automation of Electric Power Systems Press.

引用

页码：119 / 129

页数：10

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