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基于复杂网络理论的多电压交流系统直流偏磁分布关键站点识别

Critical substation identification of DC bias current distribution based on complex network theory

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【作者】 朱爽王硕周加斌马骁壮陈玉峰吴伟丽

【Author】 ZHU Shuang;WANG Shuo;ZHOU Jiabin;MA Xiaozhuang;CHEN Yufeng;WU Weili;School of Electrical and Electronic Engineering,Shandong University of Science and Technology;Power Research Institute,State Grid Shandong Electric Power Company;College of Electrical and Control Engineering,Xi’an University of Science & Technology;Anhui Zheng-Guang-Dian Electric Power Technology Co.,Ltd.;

【通讯作者】 吴伟丽;

【机构】 山东理工大学电气与电子工程学院国家电网山东省电力公司电力科学研究院西安科技大学电气与控制工程学院安徽正广电电力技术有限公司

【摘要】 为了有效治理全网范围内变压器直流偏磁,提出了基于复杂网络理论的偏磁电流分布关键节点辨别方法。首先,定义了偏磁电流节点贡献度的概念,用以反映变电站节点对与其相连的支路和节点偏磁电流分布的影响程度;其次,定义了直流偏磁治理效应指标,用以衡量关键节点识别的有效性,并提出了基于复杂网络理论的关键变电站识别方法与流程;最后,基于某实际电网的结构与参数构建复杂网络模型,对影响偏磁电流分布的变电站节点重要性进行识别。结果表明了方法的有效性和正确性,可为治理变压器直流偏磁提供有用参考。

【Abstract】 Identifying the key substation nodes that affect the distribution of the partial-magnetic current in the AC system is very vital to control effectively the transformer DC bias in the whole network.In view of this,a key node identification method based on the complex network theory is proposed.Firstly,the concept of the partial-magnetic current node contribution degree is defined to reflect the influence of substation node on the bias current distribution of the connected branches and nodes.Secondly,the index of DC bias control effect is defined to measure the effectiveness of key node identification,and a critical substation identification method and process based on complex network theory are proposed.Finally,a complex network model is constructed based on the structure and parameters of a real power grid,and the importance of the substation nodes affecting the distribution of DC bias current is distinguished,and the results show that the validity and correctness of the method.Those can provide a useful reference for the treatment of transformer DC bias.

【基金】 西安科技大学博士启动金资助项目(2017QDJ033);新疆维吾尔自治区科技厅面上资助项目(2017D01C417)
  • 【文献出处】 中国科技论文 ,China Sciencepaper , 编辑部邮箱 ,2018年23期
  • 【分类号】TM721
  • 【被引频次】2
  • 【下载频次】101
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