A Parallel Computation Algorithm for Static State Estimation by Means of Matrix Inversion Lemma

This paper presents an effective parallel computation algorithm for the static state estimation of a power system. The proposed algorithm makes use of the matrix inversion lemma and assumes the use of a MIMD type computer system. The optimal block-partitioning algorithm which tears a power system into several blocks is presented and its clear difference from that for the load flow is clarified. Simulation results on systems of up to 135 nodes have demonstrated the algorithm is very promising to the speed up of the state estimation.