Block QR decomposition based power system state estimation algorithm

This paper presents a new approach for the solution of the equality constrained power system state estimation problem. Virtual measurements are treated as equality constraints to avoid the numerical ill-conditioning problem due to the disparity in weighting factors. Triangular factorization of the coefficient matrix is carried out by performing QR decomposition on two partitioned matrices and by solving a linear equations set involving a sparse triangular matrix. Compared with normal equations with constraints method, the proposed method circumvents the cross product of the Jacobian matrix, which can cause the loss of information. In sparse QR decomposition based on Givens transformation, variable pivot row and column ordering techniques are used to reduce fill-ins and then computation efficiency is enhanced. Simulation results have shown that proposed method is stable and robust.