Development and multi-utility of an ANN model for an industrial gas turbine

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Bibliographic Details
Title: Development and multi-utility of an ANN model for an industrial gas turbine
Authors: Fast, M.1 magnus.fast@energy.lth.se, Assadi, M.1 mohsen.assadi@energy.lth.se, De, S.2 de_sudipta@rediffmail.com
Source: Applied Energy. Jan2009, Vol. 86 Issue 1, p9-17. 9p.
Subjects: Electric power, Electric generators, Natural gas, Turbines
Abstract: Abstract: Demonstration of different utilities for industrial use of an artificial neural network (ANN) model for a gas turbine has been reported in this paper. The ANN model was constructed with the multi-layer feed-forward network type and trained with operational data using back-propagation. The results showed that operational and performance parameters of the gas turbine, including identification of anti-icing mode, can be predicted with good accuracy for varying local ambient conditions. Different possible applications of this ANN model were also demonstrated. These include instantaneous gas turbine performance estimation through a graphical user interface and extrapolation beyond the range of training data. [Copyright &y& Elsevier]
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Database: Engineering Source
Description
Abstract:Abstract: Demonstration of different utilities for industrial use of an artificial neural network (ANN) model for a gas turbine has been reported in this paper. The ANN model was constructed with the multi-layer feed-forward network type and trained with operational data using back-propagation. The results showed that operational and performance parameters of the gas turbine, including identification of anti-icing mode, can be predicted with good accuracy for varying local ambient conditions. Different possible applications of this ANN model were also demonstrated. These include instantaneous gas turbine performance estimation through a graphical user interface and extrapolation beyond the range of training data. [Copyright &y& Elsevier]
ISSN:03062619
DOI:10.1016/j.apenergy.2008.03.018