Generating High Quality Pseudo-Measurements to Keep State Estimation Capabilities

Author

Filho, Milton Brown Do Coutto ; De Souza, Julio C Stacchini ; Schilling, Marcus Th

Author_Institution

Inst. of Comput., Fluminense Fed. Univ., Niteroi

fYear

2007

Firstpage

1829

Lastpage

1834

Abstract

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.

Keywords

artificial intelligence; load forecasting; neural nets; power engineering computing; power system measurement; power system state estimation; IEEE24 bus test system; artificial neural network; high quality pseudo-measurements; one-step-ahead forecasting; power systems state estimation; Artificial neural networks; Control systems; Observability; Pollution measurement; Power system modeling; Power system reliability; Predictive models; Redundancy; State estimation; System testing; control centers; data redundancy; real-time monitoring; state estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Tech, 2007 IEEE Lausanne

Conference_Location

Lausanne

Print_ISBN

978-1-4244-2189-3

Electronic_ISBN

978-1-4244-2190-9

Type

conf

DOI

10.1109/PCT.2007.4538595

Filename

4538595