刘瑞环, 陈晨, 叶志刚, 别朝红. 基于无人机应急通信的配电网灾后信息物理协同恢复策略[J]. 电网技术, 2023, 47(3): 1218-1229. DOI: 10.13335/j.1000-3673.pst.2022.0913
引用本文: 刘瑞环, 陈晨, 叶志刚, 别朝红. 基于无人机应急通信的配电网灾后信息物理协同恢复策略[J]. 电网技术, 2023, 47(3): 1218-1229. DOI: 10.13335/j.1000-3673.pst.2022.0913
LIU Ruihuan, CHEN Chen, YE Zhigang, BIE Zhaohong. Cooperative Cyber-physical Distribution System Restoration With UAV-based Emergency Communication UAV After Disasters[J]. Power System Technology, 2023, 47(3): 1218-1229. DOI: 10.13335/j.1000-3673.pst.2022.0913
Citation: LIU Ruihuan, CHEN Chen, YE Zhigang, BIE Zhaohong. Cooperative Cyber-physical Distribution System Restoration With UAV-based Emergency Communication UAV After Disasters[J]. Power System Technology, 2023, 47(3): 1218-1229. DOI: 10.13335/j.1000-3673.pst.2022.0913

基于无人机应急通信的配电网灾后信息物理协同恢复策略

Cooperative Cyber-physical Distribution System Restoration With UAV-based Emergency Communication UAV After Disasters

  • 摘要: 极端自然灾害的发生使得配电网面临电力故障和通信中断带来的复杂场景,给配电网灾后恢复带来挑战。电力通信系统的恢复对于以配电自动化为基础的配电网恢复具有重要的支撑作用,然而,现有研究并未考虑通信层恢复及其与电力恢复之间的耦合关系,进而无法有效解决在通信设施受损情况下配电网恢复过程中不同任务的协同配合问题。该文通过挖掘信息层应急通信资源的灵活性,综合考虑配电网信息层与物理层的恢复决策,提出了一种基于无人机应急通信的两阶段配电网信息物理协同恢复策略。第一阶段解决无人机基站部署选址问题,第二个阶段求解无人机通信路径规划以及配电网负荷协同恢复优化模型。提出的协同恢复模型被建模为混合整数线性规划模型,求解生成无人机的最优路径、配电网负荷恢复最优顺序,在IEEE测试系统上验证所提方法的有效性。

     

    Abstract: The distribution system restoration (DSR) is faced with difficulties brought about by a power failure and communication interruption under the extreme disasters. The recovery of the communication system plays an important role in supporting the restoration of the distribution network based on the distribution automation. However, in the existing DSR practices, the communication recovery and its interdependent relationship with the distribution system restoration are not fully considered. Therefore, it is difficult to achieve the seamless coordination among multiple DSR tasks after the communication facilities are damaged. In this paper, a two-staged cyber-physical coordination restoration strategy of the distribution network based on the emergency communication unmanned aerial vehicles (UAVs) is proposed by exploiting the emergency communication resources of the cyber layer and combining with the recovery measures in the physical layer to enhance the power system resilience. The first stage aims to locate the UAV sites, while the second stage plans the UAV routing and builds the DSR coordination optimization model. The proposed model is formulated as a mixed-integer linear programming one, which is solved to generate the optimal routes of the UAVs and the restoration sequences of loads. The effectiveness of the proposed method is evaluated on the IEEE test feeder.

     

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