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Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Comp. y Sist. vol.13 n.1 Ciudad de México Jul./Sep. 2009




Probabilistic Intelligent Systems for Thermal Power Plants


Sistemas Inteligentes Probabilistas para Plantas Termoeléctricas


Pablo Héctor Ibargüengoytia, Alberto Reyes and Zenón Flores


Instituto de Investigaciones Eléctricas, Av. Reforma 113, Palmira, Cuernavaca, Mor., 62490, México; , ,


Article received on July 16, 2008
Accepted on April 03, 2009



Artificial Intelligence applications in large–scale industry, such as thermal power plants, require the ability to manage uncertainty because current applications are large, complex and influenced by unexpected events and their evolution in time. This paper shows some of the efforts developed at the Instituto de Investigaciones Eléctricas (IIE) to assist operators of thermal power plants in the diagnosis and planning tasks using probabilistic intelligent systems. A diagnosis system, a planning system and a decision support system are presented. The diagnosis system is based on qualitative probabilistic networks, and the decision support system uses influence diagrams. The planning system is based on the Markov Decision Processes formalism. These approaches were validated in different power plant applications. Current results have shown that the use of probabilistic techniques can play an important role in the design of intelligent support systems for thermal power plants.

Keywords: power plants, diagnosis, probabilistic reasoning, Bayesian networks, influence diagrams, Markov decision processes.



Las aplicaciones de Inteligencia Artificial (IA) en industrias de gran escala, como las centrales generadoras termoeléctricas, requieren de la habilidad de manejar incertidumbre ya que estas aplicaciones son complejas e influenciadas por eventos inesperados que evolucionan en el tiempo. Este artículo muestra algunos de los esfuerzos desarrollados en el Instituto de Investigaciones Eléctricas (IIE) para apoyar a los operadores de plantas termoeléctricas en sus tareas de planeación y diagnóstico, usando sistemas inteligentes probabilistas. Se presentan en este artículo un sistema de diagnóstico, un sistema de planificación y un sistema de soporte a las decisiones. El sistema de diagnóstico está basado en redes probabilistas cualitativas y el sistema de diagnóstico en diagramas de influencia. El sistema de planificación está basado en el formalismo de los procesos de decisión de Markov. Estos tres sistemas fueron validados en diferentes aplicaciones dentro de la operación de la planta termoeléctrica. Los resultados obtenidos muestran que las técnicas probabilistas pueden jugar un importante papel en el diseño de sistemas de ayuda en la operación de plantas termoeléctricas.

Palabras clave: Plantas termoeléctricas, diagnóstico, razonamiento probabilista, redes Bayesianas, diagramas de influencia, procesos de decisión de Markov.





Thanks to the anonymous referees for their comments which improved this article. This research is supported by grants from IIE under infrastructure projects 12941 and 11984.



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