Title :
Bad data identification when using ampere measurements
Author :
Abur, Ali ; Expósito, Antonio Gómez
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
5/1/1997 12:00:00 AM
Abstract :
Earlier papers have shown that the use of power system line current magnitude measurements may lead to nonuniquely 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 nonuniquely 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
Keywords :
electric current measurement; least squares approximations; measurement errors; power system analysis computing; power system measurement; power system state estimation; ampere measurement errors; bad data identification; bad data processing methods; computer simulation; least absolute value estimation method; least squares estimation method; measurement criticality; nonuniquely observable cases; outlier rejection problem; post estimation problem; power system line current magnitude measurements; Current measurement; Data processing; Distortion measurement; Electric variables measurement; Lead; Least squares approximation; Observability; Power measurement; Power system measurements; State estimation;
Journal_Title :
Power Systems, IEEE Transactions on
