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一种基于割集断面树的电网关键输电断面搜索方法

A Search Method for Key Transmission Sections in Power Grid Based on Cut Set Section Tree
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摘要 关键输电断面是大电网运行调度中的重点监控环节。运行方式分析中需要有效的搜索算法识别关键输电断面,以便调度人员提前掌握和预判系统可能存在的热稳定风险。为此,提出了一种基于割集断面树的电网关键断面搜索方法,可以实现快速准确的关键断面搜索。首先在图模型中搜索桥结构,实现图模型简化;其次根据线路间开断灵敏度和潮流方向一致性构造断面构成关系矩阵,提出了割集断面树的定义和构造方法;最后,结合重过载辨识,实现了具有割集性质的电网热稳定关键断面搜索。IEEE 39节点系统的测试结果表明:所提方法可以快速准确地得到电网的关键断面,相比现有方法得到的断面结果更加全面。 The key transmission cross-section are key monitoring links in the operation and scheduling of large power grids.Effective search algorithms are needed in operation mode analysis to identify key transmission sections,so that dispatchers can grasp and predict potential thermal stability risks in the system in advance.To this end,a key section search method for power grids based on cut set section trees was proposed,which can achieve fast and accurate key section search.Firstly,the bridge structure was searched for in the graph model to simplify the graph model;secondly,based on the sensitivity of line interruptions and the consistency of power flow direction,a relationship matrix of section composition was constructed,and the definition and construction method of cut set section tree were proposed;finally,combined with heavy overload identification,a key section search for power grid thermal stability with cut set properties was achieved.The test results on the IEEE 39 node system show that the proposed method can quickly and accurately obtain key sections of the power grid,which is more comprehensive than the cross-sectional results obtained by existing methods.
作者 向川 李永哲 马遵 陈勇 邓灿 Xiang Chuan;Li Yongzhe;Ma Zun;Chen Yong;Deng Can(Electric Power Research Institute,Yunnan Power Grid Co.,Ltd.,Kunming Yunnan 650217,China;School of Electric Power Engineering,Guangzhou Guangdong 510640,China)
出处 《电气自动化》 2024年第4期50-52,共3页 Electrical Automation
基金 国家自然科学基金资助项目(52077080) 云南电网有限责任公司科技项目(056200KK52220044)。
关键词 关键断面 割集搜索 潮流方向一致性 开断潮流 割集断面树 key transmission section cut set search power flow direction consistency outage load flow cut section tree
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