Bad data pre-filter for state estimation

Systematic approach for pre-filter for state estimation based on wavelet analysis to detect and eliminate bad data, is developed in this work. Unbiased (random/Gaussian) bad data such as, transient meter failures, transient meter malfunction, and measurements captured during system transients, are inherently in the form of large abrupt change of short duration in a measurement-sequence. These should be detected in pre-filtering stage because their presence poses an extra burden on post-SE bad data analysis. The test results of the proposed pre-filter on two test systems establish that there is a significant reduction in the number of iterations required for bad data detection and elimination.