SHS Web Conf.
Volume 93, 20213rd International Scientific Conference on New Industrialization and Digitalization (NID 2020)
|Number of page(s)||7|
|Section||New Industrial Technologies and Innovations - The Imperative of New Industrialization and Digitalization|
|Published online||12 January 2021|
Obtaining a Neural Network Mathematical Model That Takes Into Account Various Power Supply Schemes
Perm National Research Polytechnic University, 614990 Perm, Russia
* Corresponding author: firstname.lastname@example.org
Gas turbine units are widely used as a drive for a synchronous generator in a gas turbine power plant. The main problem here lies in the fact that the control systems of such gas turbine plants are transferred practically unchanged from their aviation counterparts. This situation leads to inefficient operation of the gas turbine power plant, which affects the quality of electricity generation. To solve this problem, it is necessary to improve the control algorithms for the automatic control systems of gas turbine plants. When solving this problem, gas turbine plants should be considered in interaction with other subsystems and units; for gas turbine power plants, this is, first of all, an electric generator and the electric power system as a whole. Setting up a control system is one of the most costly stages of their production, both in terms of finance and time. Especially time-consuming operations are non-automated manual configuration management system for developmental and operational testing. Therefore, it is proposed to use a software-modeling complex, on the basis of which it is possible to obtain a neural network mathematical model of a gas turbine power plant and conduct its tests.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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