PublicationsAn Intelligent Assistant for Power Plants based on Factored MDPsAlberto Reyes, Matthijs T. J. Spaan, and L. Enrique Sucar. An Intelligent Assistant for Power Plants based on Factored MDPs. In Int. Conf. on Intelligent System Applications to Power Systems, 2009. DownloadAbstractMaking good operation decisions during abnormal power plant conditions represents in many cases the possibility to avoid a unit trip or having economical losses. This paper introduces AsistO, an intelligent assistant for the decision support based on decision theoretic planning techniques. It provides power plant operators with useful recommendations to (i) maintain a plant running under safe conditions, or (ii) deal with process transients when an unexpected event occurs. We present the formalism of Markov decision processes as the core of the intelligent assistant which uses a factored representation of plant states. We also show a very intuitive algorithm to approximate decision models based on training data collected through random exploration routines in a simulated environment. We have tested our system in the steam generation system of a combined power plant to deal with load disturbances. BibTeX Entry@InProceedings{Reyes09isap, author = {Alberto Reyes and Matthijs T. J. Spaan and Sucar, L. Enrique}, title = {An Intelligent Assistant for Power Plants based on Factored {MDPs}}, booktitle = {Int.\ Conf.\ on Intelligent System Applications to Power Systems}, year = 2009 } Note: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Generated by bib2html.pl (written by Patrick Riley) on Tue Sep 06, 2011 11:22:28 UTC |