摘要
传统状态追踪方法一般基于扩展卡尔曼滤波方法求解,其缺点是:由于电力系统量测方程的非线性,使得这些方法在求解的过程中必须对量测方程进行近似线性化,从而影响了估计精度,尤其是相邻断面的状态变量发生突变时,估计精度明显降低;传统方法在迭代的每一步中均需重新形成雅可比矩阵,因而计算效率较低。以上缺点影响了传统状态追踪方法的应用。提出一种基于精确线性化量测方程的线性状态追踪方法,所提方法的优点为:在估计中无量测方程的近似线性化误差,因而估计精度较高;在迭代中雅可比矩阵均为常数矩阵,从而提高了计算效率。通过在IEEE系统上的仿真算例验证了所提方法的有效性和高效性。
In general, traditional state tracking （ST） methods are formulated and solved by extended Kalman filter （EKF）, and their disadvantages are as follows： the first, due to the nonlinearity of power system measurement equations, it is necessary for traditional methods to make linear approximation of power system measuring equations during the solution process, thus the estimation accuracy is affected, especially when the abrupt change occurs between two adjacent measurement snapshots the estimation accuracy obviously decreases; the second, according to the traditional methods during each step of the iteration it is necessary to re-form Jacobian matrix, so the computation efficiency is lower. Since above-mentioned disadvantages affect the application of traditional ST methods, an accurate linearized measurement equation based linear ST method is proposed. The advantages of the proposed method are as follows： in the estimation no linear approximation is needed due to the accurate linearization of the measurement equations, so the estimation accuracy is higher; in the iteration all Jacobian matrices are constant thus the computation efficiency can be improved. Both effectiveness and high efficiency of the proposed method are validated by results of simulation on IEEE benchmark systems.
出处
《电网技术》
EI
CSCD
北大核心
2015年第2期472-477,共6页
Power System Technology
基金
国家高技术研究发展计划资助项目(2012AA050208)
国家自然科学基金项目(51407069)
中央高校基本科研业务费专项资金资助项目(2014QN02)~~
作者简介
陈艳波（1982），男，博士，讲师，通信作者，主要研究方向为电力系统状态估计、电力系统稳定与控制，E-mail：yanbochen2008@sina．com；
陈茜（1991），女，硕士研究生，主要研究方向为电力系统状态估计，E-mail：chenqian0407@gmail．com；
马进（1975），男，博士，教授，主要研究方向为电力系统稳定与控制。
