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1.湖南大学电气与信息工程学院,湖南省长沙市 410082
2.电能高效高质转化全国重点实验室(湖南大学),湖南省长沙市 410082
3.电力传输与功率变换控制教育部重点实验室,上海非碳基能源转换与利用研究院(上海交通大学),上海市 200240
4.国网湖南省电力有限公司防灾减灾中心(电网防灾减灾全国重点实验室),湖南省长沙市 410129
Received:20 May 2025,
Revised:2025-08-19,
Online First:09 September 2025,
Published:25 January 2026
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仇世元,周全,张轩等.山火灾害下天地一体化配电系统信息物理协同恢复策略[J].电力系统自动化,2026,50(2):46-59.
QIU Shiyuan,ZHOU Quan,ZHANG Xuan,et al.Integrated Satellite-Terrestrial Cyber-Physical Collaborative Restoration Strategy for Distribution Systems Under Wildfire Disasters[J].Automation of Electric Power Systems,2026,50(2):46-59.
仇世元,周全,张轩等.山火灾害下天地一体化配电系统信息物理协同恢复策略[J].电力系统自动化,2026,50(2):46-59. DOI: 10.7500/AEPS20250520008.
QIU Shiyuan,ZHOU Quan,ZHANG Xuan,et al.Integrated Satellite-Terrestrial Cyber-Physical Collaborative Restoration Strategy for Distribution Systems Under Wildfire Disasters[J].Automation of Electric Power Systems,2026,50(2):46-59. DOI: 10.7500/AEPS20250520008.
山火灾害发生后,快速掌握灾情并合理调度应急资源,有助于缩短配电系统恢复时间,实现重要负荷快速恢复。为加速配电系统灾后恢复进程,引入融合低轨卫星互联网的天地一体化网络架构,构建信息感知-火情响应-负荷恢复的三层恢复体系,并以最小化负荷损失、感知时间与卫星终端部署成本为目标,提出山火灾害下配电系统信息物理协同恢复模型。首先,构建多源耦合火点监测模型,评估灾区火情等级与传播趋势;其次,协同空中与地面灭火队伍,建立多约束灭火调度模型,优化火源扑灭路径与时间;然后,提出考虑节点状态可知性、电源拓扑可达性及低轨卫星通信终端部署策略的负荷恢复模型。最后,采用线性化的两阶段优化方法提升求解效率。基于IEEE 33节点系统与10节点感知网络进行了仿真,结果验证了所提方法在缩短恢复时间、提升恢复总量与优化资源配置方面的有效性与优越性。
Following a wildfire disaster
quickly grasping the disaster situation and reasonably dispatching emergency resources can help shorten the restoration time of the distribution system and achieve the rapid restoration of critical loads. To expedite the post-disaster restoration process of the distribution system
an integrated satellite-terrestrial network (ISTN) architecture based on low earth orbit (LEO) satellite internet is introduced to build a three-layer restoration framework
encompassing information perception
fire response
and load restoration. With the objective of minimizing load loss
perception time and satellite terminal deployment cost
a cyber-physical collaborative restoration model of the distribution system under wildfire disasters is proposed. Firstly
a multi-source coupled fire detection model is constructed to evaluate fire levels and propagation trends in the disaster area. Secondly
the aerial and ground firefighting teams are coordinated to establish a multi-constraint firefighting dispatching model for optimizing the fire extinguishing paths and time. Then
a load restoration model is proposed that considers node state knowability
power topology accessibility
and LEO satellite communication terminal deployment strategies. Finally
a linearized two-stage optimization method is used to improve the solving efficiency. Simulations are conducted on the IEEE 33-bus system and a 10-bus sensing network
and the results validate the effectiveness and superiority of the proposed method in terms of shortening restoration time
enhancing total restoration capacity
and optimizing resource allocation.
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