Professor Ali Abur will give a WebEx presentation on "Efficient Detection of Parameter Errors" on Dec. 3rd at 2pm EST. This is part of the ongoing monthly progress series for CURENT Industry Members.
Title: Efficient Detection of Parameter Errors
Abstract: Accuracy of the network parameters has a strong influence on the results of power system state estimation as well as all other application functions that use network model and are executed at the control centers. We have shown earlier that normalized Lagrange multipliers can be used to effectively detect and identify errors in network parameters. However, this approach carries a rather heavy computational burden limiting its practical utilization to small size systems. Thus, we have recently developed a computationally efficient algorithm to address this limitation. The idea is to derive and compute only the necessary subset of the gain matrix and covariance matrix, thus avoiding the computation and storage of large dense matrices. The proposed efficient procedure can be applied either to the single-scan or multiple-scan schemes with equal ease. Test results confirm that the improvements in computational speed and memory requirements brought by the proposed algorithm are quite remarkable. Proposed implementation of the normalized Lagrange multipliers method is tested using IEEE test systems as well as a large utility power system. In this talk, we will also discuss the effectiveness and limitations of the single-scan scheme, and the improvements brought by incorporating multiple measurement scans in detail.