摘要
在构建电力系统安全风险评估指标的基础上,提出了一种基于模式识别的支路重要性评估方法。使用ISODATA算法对支路退运的三维风险进行自组织聚类,确定各条支路的重要性等级,然后利用PCA主成分分析方法确定所有支路风险的主成分,实现数据降维后支路的重要性排序及其重要性程度分级,为核心骨干网架构建提供理论依据。采用IEEE39节点系统算例验证了该方法的有效性。该方法也适用于IEEE118节点系统,以及实际复杂电网系统。
Based on the construction of risk assessment index of power system,this paper proposes an assessment method of branch importance based on pattern recognition.Firstly,the paper uses ISODATA algorithm to carry out self-organizing clustering for the three-dimensional risk of branch outage,with the importance level of each branch determined,and then employs the principal component analysis(PCA)to determine the principal components of all the branch risks,and realize the order of importance and the classification of importance degree of branches after data dimension reduction,which provides a theoretical basis for the construction of core backbone network framework.Finally,the paper uses an IEEE39 node system as example to verify the effectiveness of the proposed method.This method is also applicable to IEEE118 node system and actual complex power grid system.
作者
赵一婕
辛巍
范杨
程绳
ZHAO Yijie;XIN Wei;FAN Yang;CHENG Sheng(Wuhan Innovation Center,AVIC Aerospace Life-Support Industries,Co.,Ltd.,Wuhan Hubei 430000,China;Maintenance Company of State Grid Hubei Electric Power Co.,Ltd.,Wuhan Hubei 430070,China)
出处
《湖北电力》
2021年第3期82-88,共7页
Hubei Electric Power
