Title :
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
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;
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
DOI :
10.1109/PCT.2007.4538595
