A continually online trained neurocontroller for excitation and turbine control of a turbogenerator

被引：80

作者：

Venayagamoorthy, GK ^{[1
]}

Harley, RG

机构：

[1] ML Sultan Technikon, Durban, South Africa

[2] Univ Natal, ZA-4001 Durban, South Africa

[3] Georgia Inst Technol, Atlanta, GA 30332 USA

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 2001年 / 16卷 / 03期

基金：

新加坡国家研究基金会;

关键词：

continual online training; neurocontroller; neuroidentifier; turbogenerator control;

D O I：

10.1109/60.937206

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of turbogenerators. This paper presents the design of a Continually Online Trained (COT) Artificial Neural Network (ANN) based controller for a turbogenerator connected to the infinite bus through a transmission line. Two COT ANNs are used for the implementation; one ANN, the neuroidentifter, to identify the complex nonlinear dynamics of the power system and the other ANN, the neurocontroller, to control the turbogenerator. The neurocontroller replaces the conventional automatic voltage regulator (AVR) and turbine governor. Simulation and practical implementation results are presented to show that COT neurocontrollers can control turbogenerators under steady state as well as transient conditions.

引用

页码：261 / 269

页数：9

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