Data debugging for real-time power system monitoring based on pattern analysis

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.

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