BAD DATA IDENTIFICATION WHEN USING AMPERE MEASUREMENTS

Earlier papers have shown that the use of line current magnitude measu rements may lead to non-uniquely observable systems. This paper studie s the bad data identification problem under these conditions. The defi nition of measurement criticality is revised in order to account for t he non-uniquely observable cases. The problem of bad data identificati on is investigated both as a post estimation problem when using the le ast squares estimation method and as an outlier rejection problem when using the least absolute value estimation method. Modifications to th e existing bad data processing methods are proposed in order to accoun t for the current magnitude measurements.