基于分块雅可比矩阵的最小二乘状态估计算法

提出了一种基于分块雅可比矩阵的加权最小二乘状态估计算法。该方法将全部的注入功率量测、赋予很大权值的虚拟量测和必要的支路量测来构造一组恰好可求解系统全部状态变量的量测集,将余下的支路功率量测作为量测系统的冗余部分看待,并依此对量测雅可比矩阵进行分块,在此基础上推导出了该文算法迭代的修正方程式。该文所提算法既具有很好的数值稳定性,又能够减少计算量。仿真试验表明该方法是快速且数值稳定。

A weighted least squares method for state estimation based on block Jacobian matrix

This paper presents a weighted least squares method for state estimation based on block Jacobian matrix. In the proposed method, whole injection measurements, highly weighted virtual measurements and a few essential flowts make up measures which can be used for resolving all state variables of a power system, while other flow measurements are considered redundant to resolve state variables. In the following, the Jacobian matrix is divided into two blocks and the iterative formula is introduced. The experiment proves that the proposed algorithm can reduce caleulatinn in normal redundant level of measure configure and has good numerical stability.