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

被引：0
|
作者：
Kavalerov B.V. [1 ]
Bakhirev I.V. [1 ]
Kilin G.A. [1 ]
机构：
[1] Perm National Research Polytechnic University, Perm
来源：
Russian Electrical Engineering | 2022年 / 93卷 / 11期
基金：
俄罗斯基础研究基金会;
关键词：
automatic tuning; gas-turbine plant; gas-turbine power plant; neural network; neural-network model; power plant;
D O I：
10.3103/S1068371222110050
中图分类号：
学科分类号：
摘要：
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. © 2022, Allerton Press, Inc.
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收藏
页码：712 / 717
页数：5
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