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Technical Briefs

Analyzing Solar Power Plant Performance Through Data Mining

[+] Author and Article Information
Henryk Maciejewski

 Wroclaw University of Technology, ul. Janiszewskiego 11∕17, 50-372, Wroclaw, Polandhenryk.maciejewski@pwr.wroc.pl

Loreto Valenzuela, Jesús Fernández-Reche

CIEMAT, Plataforma Solar de Almería, Carretera Senes s∕n, Tabernas, E-04200 Almería, Spain

Manuel Berenguel

Departamento de Lenguajes y Computación, Universidad de Almería, Carretera Sacramento s∕n, E-04120, Almería, Spain

Konrad Adamus, Michal Jarnicki

 Wroclaw University of Technology, ul. Janiszewskiego 11∕17, 50-372, Wroclaw, Poland

J. Sol. Energy Eng 130(4), 044503 (Sep 09, 2008) (3 pages) doi:10.1115/1.2969817 History: Received September 22, 2007; Revised November 13, 2007; Published September 09, 2008

This work is devoted to application of data mining methods for monitoring of state of a solar thermal plant. The methods discussed are illustrated by example of a study performed for the DISS direct steam generation facility at the Plataforma Solar de Almeria (Spain). In order to deal with the problems of large dimensionality and high correlation among the data the methods of latent variables, principal component analysis and partial least squares, were applied. Results showed that normal and abnormal states during plant operation could be identified.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Diagram of the current DISS facility

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Figure 2

Principal component plot for 1st and 2nd May calculated with model based on 2nd May

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Figure 3

PLS plot for 2nd May 2003

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