基于主成分分析法的电力系统同调机群识别  

Recognition of Power System Coherent Generators Based on Principal Component Analysis

作　　者：安军[1] 穆钢[2] 徐炜彬[2] 

机构地区：[1]华北电力大学电气与电子工程学院,河北省保定市071003 [2]东北电力大学微通电力系统研究室,吉林省吉林市132012

出　　处：《电网技术》2009年第3期25-28,共4页Power System Technology

基　　金：国家自然科学基金资助项目(50577004)~~

摘　　要：提出了一种基于主成分分析(principal component analysis,PCA)的电力系统同调机群分群识别方法。利用PCA可以保留源数据中的主要信息,采用发电机角速度作为源数据,可以获取协方差矩阵及协方差矩阵的特征根和特征相量,由此确定发电机角速度的主成分,然后通过比较各发电机对主成分的载荷系数实现对发电机的同调分群。中国电力科学研究院36节点纯交流系统算例表明,该方法计算简单,易于实现,避免了模型参数对分群的影响。Based on principal component analysis （PCA）, a new method to recognize the coherent generators of power system is proposed. By use of PCA the principal information in source data can be retained; and using the angular speed of generator, the covariance matrix as well as its characteristic roots and eigenvectors can be obtained, and from this the principal component of angular speed of generator can be determine; thus comparing the load coefficient of each generator to the principal component the coherency identification of generators can be implemented. The calculation results of EPRI-36bus pure AC power system show that the proposed method is simple to calculate and easy to implement, and the affects of model parameters can be avoided.

关 键 词：分群 同调机群 主成分分析(PCA) 电力系统 

分 类 号：TM743[电气工程—电力系统及自动化]