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Gas-Turbine Power-Plant Neural-Network Models for Synthesis and Tuning of Control Systems

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Abstract

This article discusses the possibility of using neural-network models of gas-turbine power plants for automatic tuning and synthesis of control systems. The considered neural-network models represent a gas-turbine plant and a synchronous generator as a single model of a gas-turbine power plant. The rationale for the architecture of an artificial neural network is given, which, after training, is capable of reproducing the operation of gas-turbine power plants with various configurations of electric-power systems. The results of the application of a neural-network model of a gas-turbine power plant for automatic tuning of the free-turbine speed-control loop are presented. The results of mathematical modeling confirming the effectiveness of the method are presented.

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Funding

This study was carried out with the financial support of the Russian Foundation for Basic Research and Perm krai within the framework of scientific project no. 19-48-590012.

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Authors and Affiliations

  1. Perm National Research Polytechnic University, 614990, Perm, Russia

    B. V. Kavalerov, I. V. Bakhirev & G. A. Kilin

Authors
  1. B. V. Kavalerov
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  2. I. V. Bakhirev
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  3. G. A. Kilin
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Corresponding author

Correspondence to G. A. Kilin.

Additional information

Translated by Sh. Galyaltdinov

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Kavalerov, B.V., Bakhirev, I.V. & Kilin, G.A. Gas-Turbine Power-Plant Neural-Network Models for Synthesis and Tuning of Control Systems. Russ. Electr. Engin. 93, 712–717 (2022). https://doi.org/10.3103/S1068371222110050

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  • DOI: https://doi.org/10.3103/S1068371222110050

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