Resilience-Enhanced Optimal Placement Model of Remote-controlled Switch for Smart Distribution Network

被引：0
|
作者：
Bian Y. [1 ]
Bie Z. [1 ]
机构：
[1] School of Electrical Engineering, Xi'an Jiaotong University, Xi'an
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2021年 / 45卷 / 03期
关键词：
Network reconfiguration; Resilient distribution system; Robust optimization; Switch placement;
D O I：
10.7500/AEPS20200524001
中图分类号：
学科分类号：
摘要：
The deep fusion of cyber-physical system provides technical support for the dynamic and remote control of the distribution network. After extreme events attack the distribution network, remote-controlled switches (RCS) can isolate the faults, reduce the scope of the fault areas, and participate in the network reconfiguration to restore loads. The robust optimal model placement of RCS is proposed. The placement of RCS is completed in the planning stage to minimize the loss of load curtailment of the distribution network after extreme events. Based on the defender-attacker-defender (DAD) framework, the planner determines the plan of the placement of RCS at the first level. According to the system after planning, the attacker looks for the most serious mode of attacks at the second level. At the third level, the operator considers the impact of N-K multiple fault propagation, isolates fault through RCS and reconfigures the network to form microgrids powered by distributed generators (DG) to restore load. The three levels interact with each other to improve the load restoration effect of the distribution network in the most serious mode of attacks. The column-and-constraint generation algorithm is used to solve the model. The validity of the model is verified by the modified IEEE 37-bus system. © 2021 Automation of Electric Power Systems Press.
引用
收藏
页码：33 / 39
页数：6
相关论文
共 24 条
  • [1] BIE Zhaohong, LIN Yanling, QIU Aici, Concept and research prospects of power system resilience, Automation of Electric Power Systems, 39, 22, pp. 1-9, (2015)
  • [2] GAO Haixiang, CHEN Ying, HUANG Shaowei, Et al., Distribution systems resilience: an overview of research progress, Automation of Electric Power Systems, 39, 23, pp. 1-8, (2015)
  • [3] GAO H X, CHEN Y, MEI S W, Et al., Resilience-oriented pre-hurricane resource allocation in distribution systems considering electric buses, Proceedings of the IEEE, 105, 7, pp. 1214-1233, (2017)
  • [4] WANG Y Z, CHEN C, WANG J, Et al., Research on resilience of power systems under natural disasters-a review, IEEE Transactions on Power Systems, 31, 2, pp. 1604-1613, (2016)
  • [5] LI J, MA X Y, LIU C C, Et al., Distribution system restoration with microgrids using spanning tree search, IEEE Transactions on Power Systems, 29, 6, pp. 3021-3029, (2014)
  • [6] CHEN C, WANG J, QIU F, Et al., Resilient distribution system by microgrids formation after natural disasters, IEEE Transactions on Smart Grid, 7, 2, pp. 958-966, (2016)
  • [7] ARIF A, WANG Z Y, WANG J H, Et al., Power distribution system outage management with co-optimization of repairs, reconfiguration, and DG dispatch, IEEE Transactions on Smart Grid, 9, 5, pp. 4109-4118, (2018)
  • [8] WANG Shouxiang, LI Xiaojing, XIAO Zhaoxia, Et al., Multi-agent approach for service restoration of distribution system containing distributed generations, Automation of Electric Power Systems, 31, 10, pp. 61-65, (2007)
  • [9] MA S S, LI S Y, WANG Z Y, Et al., A novel MILP formulation for fault isolation and network reconfiguration in active distribution systems, 2018 IEEE Power & Energy Society General Meeting, (2018)
  • [10] ABIRI-JAHROMI A, FOTUHI-FIRUZABAD M, PARVANIA M, Et al., Optimized sectionalizing switch placement strategy in distribution systems, IEEE Transactions on Power Delivery, 27, 1, pp. 362-370, (2012)
123