scholarly journals Study on Synchronous Generator Excitation Control Based on FLC

2015 ◽  
Vol 03 (04) ◽  
pp. 232-239 ◽  
Author(s):  
Zhiting Guo ◽  
Hong Song ◽  
Penggao Wen ◽  
Zhizheng Fan
Keyword(s):  
Synchronous Generator ◽  
Excitation Control ◽  
Synchronous Generator Excitation ◽  
Generator Excitation Control

scholarly journals Predictive Synchronous Generator Excitation Control Based on Laguerre Model

2013 ◽  
Vol 64 (3) ◽  
pp. 173-179
Author(s):  
Jozef Škultéty ◽  
Eva Miklovičová ◽  
Ruth Bars
Keyword(s):  
Nuclear Power ◽  
Design Procedure ◽  
Synchronous Generator ◽  
Excitation Control ◽  
Control Approach ◽  
Model Reference Control ◽  
System Operator ◽  
Control Objective ◽  
Synchronous Generator Excitation ◽  
Generator Excitation Control

In this paper the synchronous generator excitation control is designed using the model reference control approach and its predictive extension. The control objective is to satisfy requirements on the synchronous generator performances imposed by the transmission system operator. The structure of both controllers is expressed in the form of modified Laguerre network. The efficiency of the proposed control design procedure is illustrated by simulation of the 259 MVA synchronous generator of the nuclear power plant Mochovce in Slovakia.

A Hybrid Intelligent Excitation Control for Ship Power Station

2011 ◽  
Vol 128-129 ◽  
pp. 780-783
Author(s):  
Zhi Peng Shen ◽  
Chen Guo ◽  
Yu Ting Wang
Keyword(s):  
Intelligent Control ◽  
Learning Algorithm ◽  
Synchronous Generator ◽  
Control Technique ◽  
Excitation Control ◽  
Power Station ◽  
Terminal Voltage ◽  
Simulation Results ◽  
Synchronous Generator Excitation ◽  
Generator Excitation Control

Hybrid intelligent control technique is used for ship power station synchronous generator excitation control in this paper. The parameters and structure of the excitation controller are learned and adjusted through a hybrid learning algorithm combining self-organizing learning with BP learning. This algorithm converges much faster than original BP learning. Simulation results show that the synchronous generator excitation controller based on the learning algorithm can significantly stabilize terminal voltage.

Sign in / Sign up

Export Citation Format

Share Document