基于区间电气DebtRank算法的含风电电力系统脆弱节点识别  

Identification of vulnerable nodes in power system containing wind power based on interval Electrical DebtRank algorithm

作　　者：李利娟[1,2] 李月 丁钢伟 吕志强 曾亦惟 Li Lijuan;Li Yue;Ding Gangwei;Liu Zhiqiang;Zeng Yiwei(College of Automation and Electronic Information,Xiangtan University,Xiangtan 411105,China;Hunan National Center for Applied Mathematics,Xiangtan University,Xiangtan 411105,China)

机构地区：[1]湘潭大学自动化与电子信息学院,湖南湘潭411105 [2]湖南国家应用数学中心,湖南湘潭411105

出　　处：《可再生能源》2025年第4期521-527,共7页Renewable Energy Resources

基　　金：国家自然科学基金(52077189)。

摘　　要：针对风电的随机性和波动性会影响电网脆弱性评估和关键节点辨识的问题,文章提出了一种区间电气DebtRank算法来识别电网中的脆弱节点。该方法首先考虑了节点的偏移状态及节点特性,改进了电气DebtRank算法;然后,用区间数表示风力发电的随机性和波动性,,提出了区间电气DebtRank算法来辨识含有风电接入电力系统情况下的脆弱节点;最后,通过IEEE-118节点系统的仿真对比分析表明,所提方法辨识的脆弱节点遭到攻击时,系统可供电能力下降到系统正常时的33%,系统的电能传输能力大幅降低。In response to the issue that the randomness and volatility of wind power can affect the vulnerability assessment of the power grid and the identification of critical nodes,this paper proposes an interval-based Electrical DebtRank algorithm to identify vulnerable nodes within the power grid.The method first incorporates the node's offset status and characteristics to improve the traditional Electrical DebtRank algorithm.Then,interval numbers are used to represent the randomness and volatility of wind power generation,leading to the development of the intervalbased Electrical DebtRank algorithm to identify vulnerable nodes in a wind-integrated power system.Finally,simulation results on the IEEE-118 bus system demonstrate that when the vulnerable nodes identified by the proposed method are attacked,the system's power supply capability drops to 33% of its normal state,with a significant reduction in the system's power transmission capacity.

关 键 词：脆弱性评估 关键节点 偏移状态 区间电气DebtRank算法 

分 类 号：TK81[动力工程及工程热物理—流体机械及工程]