scholarly journals Excitation Control of Generators for Stabilizing a Power System of Large Scale by the Model Reduction Method

1996 ◽  
Vol 116 (1) ◽  
pp. 104-113
Author(s):  
Kunio Matusita ◽  
Fujio Isiguro ◽  
Sigeru Omatu
Keyword(s):  
Power System ◽  
Model Reduction ◽  
Large Scale ◽  
Reduction Method ◽  
Excitation Control

scholarly journals Discussion: “Model Reduction of Large-Scale Discrete Plants With Specified Frequency Domain Balanced Structure” (Zadegan, A., and Zilouchian, A., 2005, ASME J. Dyn. Syst. Meas., Control, 127, pp. 486–498)

2009 ◽  
Vol 131 (6) ◽  
Author(s):  
Hamid Reza Shaker ◽  
Rafael Wisniewski
Keyword(s):  
Model Reduction ◽  
Frequency Domain ◽  
Large Scale ◽  
Reduction Method ◽  
Order Reduction ◽  
Balanced Structure ◽  
Order Reduction Method

This work presents a commentary of the article published by A. Zadegan and A. Zilouchian (2005, ASME J. Dyn. Syst. Meas., Control, 127, pp. 486–498). We show their order reduction method is not always true and may lead to inaccurate results and is therefore erroneous. A framework for solving the problem is also suggested.

Nonlinear Dynamic Power System Model Reduction Analysis Using Balanced Empirical Gramian

2013 ◽  
Vol 448-453 ◽  
pp. 2368-2374 ◽  
Author(s):  
Hong Shan Zhao ◽  
Ning Xue ◽  
Ning Shi
Keyword(s):  
Nonlinear System ◽  
Power System ◽  
Model Reduction ◽  
Reduction Method ◽  
System Model ◽  
System Dynamic Model ◽  
Lower Dimension ◽  
Input And Output ◽  
System Input ◽  
Power System Model

This paper presents an empirical Gramian balanced reduction method which efficiently solves nonlinear power system model reduction problems. This method projects the nonlinear power system dynamic model to a lower dimension subspace and the reduced model can retain the original nonlinear system input and output dynamic behaviors. A four-generator nonlinear power system, combining different factors which form empirical controllable and observable Gramian matrices, is used to analyze how external excitations and outputs affect balanced empirical Gramian reduction. The case verifies the feasibility and effectiveness of balanced empirical Gramian reduction method.

A model Reduction Method for Monitoring Large-scale Processes

2001 ◽  
Vol 34 (22) ◽  
pp. 425-430
Author(s):  
Uwe Kruger ◽  
Xun Wang ◽  
S. Joe Qin
Keyword(s):  
Model Reduction ◽  
Large Scale ◽  
Reduction Method
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