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.

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.

scholarly journals Synchronous Generator Excitation Control Based on Model Predictive Control

2021 ◽  
Author(s):  
Qingxiang Jin
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Classical Model ◽  
Synchronous Generator ◽  
Control Procedure ◽  
Excitation Control ◽  
Computationally Efficient ◽  
Terminal Voltage ◽  
Synchronous Generator Excitation ◽  
Generator Terminal

This thesis research has designed and developed an optimal predictive excitation control, named the Model Predictive Excitation Control (MPEC), for utility generators. Four significant results are achieved: First, the MPEC has been designed and has significantly improved the classical model predictive control and is much simpler and computationally efficient. Second, the MPEC simulation program and results have been accomplished, and study cases have demonstrated the effectiveness of the MPEC. Third, the Modified classical model predictive control procedure has been formulated to correct a timing error such that the controlling input for the present time is re-written as that for the next step. Fourth, the MPEC optimization formulation and procedure has been developed for the generator control with only two substation-ready-available measurements which are the generator terminal voltage and speed.

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