基于广域测量信息的同调机群快速识别算法

Fast Recognition Method for Coherent Generators Based on Wide Area Measurement Information

广域测量系统WAMS为电力系统自动化提供了有效的平台。本文基于WAMS实测转子功角信息,利用差分法计算转子角速度和角加速度,将图像匹配中角点的提取和比较应用到同调分群算法中,通过比较各发电机转子角加速度轨迹中角点的幅值和时间差异对发电机组初步分群。进而利用发电机转子角速度的离散Hausdorff距离构造同调群内无向图,利用图论聚类实现精确分群。该方法计算简单,采用自适应数据窗分群迅速,能够实现复杂系统的在线分群。本文通过EPRI-36节点系统仿真算例验证了该方法的正确性。

Wide area measurement system(WAMS)provides an effective platform for the automation of power system.In this paper,based on the power angle information measured by WAMS,the rotors’angular velocities and angular accelerations are calculated using difference algorithm.Then,the extraction and comparison of corners in image matching are applied to the coherency identification algorithm,and through the comparison of amplitude and time difference of corners on the angular acceleration trajectory among rotors in different generators,a preliminary identification of generators is obtained.Finally,discrete Hausdorff distances of the rotors’angular velocities are used to construct an undirected graph of coherent groups,and graph-theoretical clustering is used to realize a precise identification.This method is simple,and the corresponding clustering is rapid with an adaptive data window,which can realize an online identification of a complex system.An EPRI 36-node system is used as a numerical example,and simulation result verifies the validity of the proposed method.