Generating High Quality Pseudo-Measurements to Keep State Estimation Capabilities

Generating High Quality Pseudo-Measurements to Keep State Estimation Capabilities

This paper proposes a methodology for providing real-time high quality pseudo-measurements to be used by the state estimation function. A forecasting step is added to the estimation process in which one-step-ahead forecasts, obtained considering recent past state estimation results, are adopted as p...

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Hauptverfasser: Do Coutto Filho, M.B., de Souza, J.C.S., Schilling, M.T.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
control centers
Control systems
data redundancy
Observability
Pollution measurement
Power system modeling
Power system reliability
Predictive models
real-time monitoring
Redundancy
State estimation
System testing
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Beschreibung
Zusammenfassung:This paper proposes a methodology for providing real-time high quality pseudo-measurements to be used by the state estimation function. A forecasting step is added to the estimation process in which one-step-ahead forecasts, obtained considering recent past state estimation results, are adopted as pseudo-measurements. The model used to make forecasts is based on an artificial neural network. Test results using the IEEE-24 bus test system are presented to illustrate the performance of the proposed methodology.
DOI:10.1109/PCT.2007.4538595