An approach to power system branch parameter estimation

This paper proposes an off-line approach to estimate suspicious series branch parameters of power system based on historical series of data. The proposed off-line approach uses a decoupled augmented state estimator which increases the V-thetas state vector for the inclusion of suspicious series branch parameters. Normal equations approach is used to deal with the resulting augmented model. The idea is to use several measurement snapshots in order to estimate the suspicious series branch parameters in a sequential form, taking advantage of the fact that those parameters can be considered time-invariant. The proposed approach has presented a very good performance considering the occurrence of single and multiple parameter errors in adjacent and non-adjacent branches. Simulation results with the IEEE-14-bus test system show the application of the proposed approach.