Estimación de estado dinámico en sistemas eléctricos de potencia usando filtros extendidos de kalman

Ana Isabel Palacios, Carlos Barrera-Singaña

Abstract


El método para resolver problemas de Estimación de Estado utilizando filtros extendidos de Kalman en sistemas eléctricos de potencia se presenta en este trabajo. Los estimadores trabajan con información en tiempo real de diferentes dispositivos de medida instalados en el sistema y forman una base de datos que se concentra en el centro de control a través de SCADA, esta información funciona como filtros ante datos incorrectos. La técnica de mínimos cuadrados ponderados (WLS) se utiliza comúnmente para resolver el problema de estimación debido a sus propiedades estadísticas. Sin embargo, otras técnicas de estimación de estado dinámico se estructuran con diversas variaciones del filtro de Kalman. El Filtro de Kalman Extendido (EKF), como algoritmo para los sistemas no lineales de estado de estimación, es eficiente. La complejidad de la implementación, la precisión y la eficiencia del cálculo, la resistencia a los errores de medición y la sensibilidad a las escalas del sistema se analizan en un sistema estándar IEEE  de 14 barras.


Keywords


: estimadores de estado, ekf, filtros de kalman, método mínimos cuadrados ponderados, sistemas eléctricos de potencia.

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DOI: https://doi.org/10.34115/basrv6n3-023

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