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

Abstract

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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REFERENCES

  1. 1

    Gol’berg, F.D. and Batenini, A.V., Matematicheskie modeli gazoturbinnykh dvigatelei kak ob”ektov upravleniya (Mathematical Models of GTE as the Controlled Objects), Moscow: Mosk. Aviats. Inst., 1999.

  2. 2

    Asgari, H., Chen, X.Q., Menhaj, M.B., and Sainudiin, R., Artificial neural network-based system identification for a single-shaft gas turbine, J. Eng. Gas Turbines Power, 2013, vol. 135, no. 9.

  3. 3

    Asgari, H., Chen, X.Q., and Sainudiin, R., Modeling and simulation of gas turbines, Int. J. Model., Identif. Control, 2013, vol. 20, no. 3.

  4. 4

    Asgari, H. and Chen, X.Q., Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks, Boca Raton, FL: CRC Press, 2015.

    Google Scholar 

  5. 5

    Kilin, G.A., Adjesment of neural network parameters for a mathematical model of a gas turbine power plant, Materialy Mezhdunarodnoi nauchno-prakticheskoi konferentsii “Nauka segodnya: Zadachi i puti ikh resheniya” (Proc. Int. Sci.-Pract. Conf. Modern Science: Problems and Their Solutions”), Vologda: Marker, 2016.

  6. 6

    Kilin, G.A., Kavalerov, B.V., and Masyagin, E.D., The choice of neural network architecture to design a mathematical model of a gas turbine power plant, Materialy Mezhdunarodnoi nauchno-prakticheskoi konferentsii “Aktual’nye problemy elektromekhaniki i elektrotekhnologii” (Proc. Sci.-Pract. Conf. “Current Problems in Electromechanics and Electrical Technologies”), Yekaterinburg: Ural. Fed. Univ., 2017.

  7. 7

    Kilin, G.A., Bakhirev, I.V., and Kavalerov, B.V., Nonlinear GTU model receiving by neural network, Avtom. Elektroenerg. Elektrotekh., 2015, vol. 1.

    Google Scholar 

  8. 8

    Kavalerov, B.V. and Kilin, G.A., Electric gas-turbine unit control system automation tuning based on neural network models, Inf.-Izmerit. Upr. Sist., 2018, no. 9.

  9. 9

    Kilin, G.A. and Kavalerov, B.V., Development of a mathematical model of a gas turbine power plant based on neural networks, Materialy nauchno-tekhnicheskoi konferentsii “Klimovskie chteniya–2016: Perspektivnye napravleniya razvitiya aviadvigatelestroeniya” (Proc. Sci.-Tech. Conf. “Klimov’s Readings–2017: Advanced Development of Aircraft Engine Manufacturing”), St. Petersburg: Skifiya-Print, 2016.

  10. 10

    Haykin, S.S., Neural Networks: A Comprehensive Foundation, New York: Macmillan, 1994.

    Google Scholar 

  11. 11

    Callan, R., The Essence of Neural Networks, London: Prentice Hall, 1999.

    Google Scholar 

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Funding

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). https://doi.org/10.3103/S1068371220110085

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Keywords:

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