Set of Neural Network Models for Intelligent Control of Low- and Medium-Capacity Gas-Turbine Power Plants


The idea of creating a set of neural network models consists in that, due to the widespread use of distributed power generation and an increasingly frequent use of low- and medium-capacity gas-turbine power plants, it is required to ensure a stable and reliable production of electricity at required quality levels. The solution proposed to solve this task is to develop intelligent control systems and new control algorithms for gas-turbine power plants, considering the behavior of the whole structure of the electrical system on the basis of the model-oriented approach with the help of a set of neural network models. This approach opens a broad range of possibilities for studying and taking into account, first of all, the whole diversity of performance situations and design layouts of the power system and, second, the whole diversity of advanced techniques of the theory of automatic control for running individual energy modules in performance situations emerging in the energy system.

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This work was financially supported by the Russian Foundation for Basic Research and the government of Perm krai, research project 19-48-590012.

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Correspondence to G. A. Kilin.

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Translated by S. Kuznetsov

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Kilin, G.A., Kavalerov, B.V. & Suslov, A.I. Set of Neural Network Models for Intelligent Control of Low- and Medium-Capacity Gas-Turbine Power Plants. Russ. Electr. Engin. 91, 659–664 (2020).

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  • power plant
  • gas-turbine power plant
  • artificial neural networks
  • neural network models