Parameter errors and gross errors detection, identification and correction

Gross Errors and parameter errors can cause a significant degradation of the results provided by a state estimator, meanly when both appear simultaneously. The majority of methods developed to treat these errors do not consider that both appear simultaneously. This paper proposes an approach that allows detection, identification and correction of parameter errors and gross errors, even when both appear simultaneously. The proposed approach works in two Phases: Phase 1 - detection, identification and correction of network branch parameter (series and shunt admittances) errors using several measurement snapshots; and Phase 2 - gross errors detection, identification and correction. If any gross error was identified in Phase 2, Phase 1 is processed again in order to improve the quality of the parameter estimates. The proposed approach is based on previous authors´ researches whose main points will be presented in this paper. Simulation results have sown the effectiveness of the proposed approach even when the gross errors are incident to the branch with parameter errors.