Predicción de voltajes en la red eléctrica por interpolación Kriging
Enviado: 19-06-2024
|Aceptado: 18-09-2024
|Publicado: 25-09-2024
Derechos de autor 2024 Carlos Moreno-Blazquez, Filiberto Fele, Daniel Limon, Teodoro Alamo
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
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Palabras clave:
Aprendizaje para el control, Métodos no paramétricos, Redes eléctricas inteligentes, Monitoreo y control de restricciones y seguridad, Control de recursos de energía renovable, Control basado en datos
Agencias de apoyo:
Ministerio de Ciencia, Innovación y Universidades
FEDER
Universidad de Sevilla
Unión Europea
Resumen:
En este trabajo, abordamos el problema de la predicción en línea de las trayectorias de voltaje e intensidad nodales en la red de distribución. Para esto, proponemos una formulación basada en datos utilizando la interpolación Kriging, una técnica de aprendizaje automático que ha mostrado aplicaciones prometedoras en el campo del control basado en datos. Producimos un oráculo de predicción no paramétrico que permite inferir trayectorias futuras directamente a partir de medidas de voltaje e intensidad en tiempo real. Además, proporcionamos una implementación algorítmica simple pero efectiva basada en el conocido esquema ISTA. Demostramos la efectividad de nuestra metodología para la predicción rápida (subsegundos) de la dinámica del voltaje mediante simulaciones.
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