Predictive techniques applied to geothermal power plants data

Cideos Nunez, Oscar F.. Predictive techniques applied to geothermal power plants data. University of Iceland, 2015.

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Thesis
Collection:
UNU-GTP Thesis

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  • Sub-type Master's thesis
    Author Cideos Nunez, Oscar F.
    Title Predictive techniques applied to geothermal power plants data
    Year 2015
    University University of Iceland
    Department Faculty of Industrial Engineering, Mechanical Engineering and Computer Science
    Place of Publication Reykjavik
    Publisher United Nations University Geothermal Training Programme
    Pages 47
    Language eng
    Abstract An extensive operational database is usually present in any power plant and geothermal power plants are no exception, due to the amount of information that is constantly collected from sensors and measurement parameters during the normal operation. As time goes on power plants start becoming a unique structure due to the different components in the plant and also the added efficiencies that keep changing over the any component lifetime. Thermodynamic models while always reliable tend to be less accurate over time. In this research a different approach is tried on predicting a component behavior. The idea behind this research was to predict a component output (a turbine in this case) using a series of models based on all the data collected relevant to that particular component. Certain data processing needs to be done in order to start the analysis. This data processing is mostly to adapt the algorithms to the data analyzed, otherwise the process becomes straightforward. An event prediction model based on geothermal field reports was also considered to try to determine what causes anomalous behavior in the power plant.
    UNBIS Thesaurus GEOTHERMAL ENERGY
    POWER PLANTS
    THERMAL POWER PLANTS
    DATA ANALYSIS
    Keyword Data mining
    Decision trees
    Linear regression
    Big data
    Big datasets
    Operational data
    Copyright Holder United Nations University Geothermal Training Programme
    Copyright Year 2015
    Copyright type Fair use permitted
    ISBN 9789979683766
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    Created: Thu, 18 Feb 2016, 22:55:08 JST by Malfridur Omarsdottir on behalf of UNU Iceland