一种鲁棒全网暂态过程动态状态联合估计算法  

A Joint Estimation Algorithm for the Dynamic State of the Transient Process

作　　者：马安安 MA Anan(Nanjing Power Supply Company,Nanjing Jiangsu 210019)

机构地区：[1]国网南京供电公司,江苏南京210019

出　　处：《软件》2025年第3期11-13,共3页Software

基　　金：国家重点研发计划项目(2018YFB1500800)。

摘　　要：针对全网的状态估计问题,本研究对发电机状态及网络量进行离散耦合,利用无迹卡尔曼滤波技术提出了适用于电力系统的全网动态状态跟踪方法。然而,由于PMU数据的质量不高,为解决坏数据的问题,本研究通过推导残差方程得出时变的阈值,再通过迭代检测方法确定坏数据的测点位置。算例结果表明,本文方法能有效抑制量测坏数据对全网暂态过程动态状态联合估计的影响。In response to the state estimation problem of the entire network,this study discretely couples the generator state and network variables,and proposes a dynamic state tracking method suitable for the entire power system using the Unscented Kalman Filter technique.However,due to the low quality of PMU data,in order to solve the problem of bad data,this study derived a time-varying threshold through residual equation derivation,and then determined the measurement point position of bad data through iterative detection method.The calculation results show that the method proposed in this paper can effectively suppress the influence of bad measurement data on the joint estimation of dynamic states of transient processes in the entire network.

关 键 词：状态估计 PMU量测 坏数据 离散耦合 机电暂态 

分 类 号：TM761[电气工程—电力系统及自动化]