Bad data identification when using ampere measurements

Earlier papers have shown that the use of line current magnitude measurements may lead to non-uniquely observable systems. This paper studies the bad data identification problem under these conditions. The definition of measurement criticality is revised in order to account for the non-uniquely observable cases. The problem of bad data identification is investigated both as a post estimation problem when using the least squares estimation method and as an outlier rejection problem when using the least absolute value estimation method. Modifications to the existing bad data processing methods are proposed in order to account for the current magnitude measurements.