Title :
Data debugging for real-time power system monitoring based on pattern analysis
Author :
Souza, J.C.S. ; Leite da Silva, Armando M. ; Silva, A. M Leite da
Author_Institution :
Dept. of Electr. Eng., Univ. Federal Fluminense, Niteroi, Brazil
fDate :
8/1/1996 12:00:00 AM
Abstract :
This paper presents a new method for solving bad data acquisition problems in power system state estimation. The normalized innovations, available in the pre-filtering stage of a forecasting-aided state estimator, are used as input variables to a constructive artificial neural network (ANN). The ANN performs a pattern analysis in order to identify both topological and analogical errors. The performance of the method is evaluated and discussed for different types of error and operating conditions using the IEEE-24 bus system
Keywords :
data acquisition; neural nets; pattern recognition; power system analysis computing; power system measurement; power system state estimation; program debugging; real-time systems; ANN; IEEE-24 bus system; analogical errors; bad data acquisition; constructive artificial neural network; data debugging; forecasting-aided state estimator; pattern analysis; power system state estimation; pre-filtering stage; real-time power system monitoring; topological errors; Artificial neural networks; Data acquisition; Debugging; Input variables; Monitoring; Power system analysis computing; Power systems; Real time systems; State estimation; Technological innovation;
Journal_Title :
Power Systems, IEEE Transactions on
