Skip to main content
SpringerLink
Log in

Using Neural Networks in Controlling Low- and Medium-Capacity Gas-Turbine Plants

  • Published:
Russian Electrical Engineering Aims and scope Submit manuscript

Abstract

The possibilities of using neural network technologies for synthesizing new and improving existent gas-turbine plant (GTP) control systems are considered. Modern gas-turbine plant control systems are often developed on the basis of aviation automatic control systems, without taking into account the peculiarities of load changes in electricity generation. As a result, frequency-related quality indicators of electricity, such as maximum deviation and recovery time, do not always meet requirements that have been set out. This study is aimed at improving the quality of generated electricity. A list of different disturbances that can arise in an electric power system is provided, as well as the results of using the neural network model of a GTP to optimize the parameters of the gas-turbine unit adjuster.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.

Similar content being viewed by others

REFERENCES

  1. Venikov, V.A., Perekhodnye elektromekhanicheskie protsessy v elektricheskikh sistemakh (Transitional Electromechanical Processes in Electrical Systems), Moscow: Vysshaya Shkola, 1985.

  2. Kavalerov, B.V. and Basargin, Sh.D., Unified transient quality indicators for automated testing of gas turbine power plants, Fundam. Issled., 2015, no. 12-3.

  3. Kilin, G.A. and Kavalerov, B.V. A neural network mathematical model for automated testing of an automatic control system for small- and medium-size power gas turbine power plants, Sovrem. Naukoemkie Tekhnol., 2019, no. 2.

  4. 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.

  5. Zhdanovskii, E.O., Kavalerov, B.V., and Kilin, G.A., Development of neural network model of gas turbine power plant for controllers of gas-turbine installations, Fundam. Issled., 2016, no. 12-3.

  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. Kilin, G.A. and Kavalerov, B.V., Use of neural network technologies in mathematical models of the gas-turbine installation–alternator system, Materialy II Mezhdunarodnoi nauchno-tekhnicheskoi konferentsii “Avtomatizatsiya v elektroenergetike i elektrotekhnike” (Proc. II Int. Sci.-Tech. Conf. “Automation in Electrical Energetics and Electrical Engineering”), Perm: Permsk. Nats. Issl. Politekhn. Univ., 2016.

  8. Kilin, G.A., Kavalerov, B.V., and Odin, K.A., Use of genetic algorithm for adjustment and optimization of control systems of gas turbine installations, Vestn. Permsk. Nats. Issl. Politekhn. Univ. Elektrotekhn., Inf. Tekhnol., Sist. Upr., 2014, no. 2.

Download references

Funding

This study was financially supported by the Russian Foundation for Basic Research and Perm krai as part of scientific project no. 19-48-590012.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Mechanics, Perm National Research Polytechnic University, 614990, Perm, Russia

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

Authors
  1. B. V. Kavalerov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. I. V. Bakhirev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. A. Kilin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. V. Kavalerov.

Additional information

Translated by S. Kuznetsov

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kavalerov, B.V., Bakhirev, I.V. & Kilin, G.A. Using Neural Networks in Controlling Low- and Medium-Capacity Gas-Turbine Plants. Russ. Electr. Engin. 90, 737–740 (2019). https://doi.org/10.3103/S106837121911004X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S106837121911004X

Keywords:

Search

Navigation