An Orthogonal Row Processing Algorithm for Power System Sequential State Estimation

Abstract

In this paper a sequential algorithm for power system state estimation based on the use of Givens rotations is investigated. The fact that the rotations are orthogonal transformations assures the numerical stability of the algorithm. The Jacobian matrix is processed one row at a time, and sparsity can be easily exploited. Also, the method presents some features which are advantageous from the point of view of bad data detection, identification and elimination. Both the description and the implementation of a fast version of the Givens rotations are presented. The method is applied to three different power systems, including real size networks, and the results are used to assess its performance.