Power system stabilizers design using optimal reduced order models. I. Model reduction

1988 ◽  
Vol 3 (4) ◽  
pp. 1670-1675 ◽  
Author(s):  
A. Feliachi ◽  
X. Zhang ◽  
C.S. Sims
Keyword(s):  
Power System ◽  
Model Reduction ◽  
Reduced Order Models ◽  
Power System Stabilizers ◽  
Reduced Order

A Physics-Based Dynamic Model for Boilers: Part 2 — Model Reduction in a Cogeneration Application

2017 ◽  
Author(s):  
Matthew J. Blom ◽  
Michael J. Brear ◽  
Chris G. Manzie ◽  
Ashley P. Wiese
Keyword(s):  
Model Reduction ◽  
Gas Turbine ◽  
Dynamic Model ◽  
Reduction Process ◽  
Singular Perturbation Theory ◽  
Reduced Order Models ◽  
Reduced Order ◽  
One Dimensional ◽  
Time Scale Separation ◽  
Modelling Framework

This paper is the second part of a two part study that develops, validates and integrates a one-dimensional, physics-based, dynamic boiler model. Part 1 of this study [1] extended and validated a particular modelling framework to boilers. This paper uses this framework to first present a higher order model of a gas turbine based cogeneration plant. The significant dynamics of the cogeneration system are then identified, corresponding to states in the gas path, the steam path, the gas turbine shaft, gas turbine wall temperatures and boiler wall temperatures. A model reduction process based on time scale separation and singular perturbation theory is then demonstrated. Three candidate reduced order models are identified using this model reduction process, and the simplest, acceptable dynamic model of this integrated plant is found to require retention of both the gas turbine and boiler wall temperature dynamics. Subsequent analysis of computation times for the original physics-based one-dimensional model and the candidate, reduced order models demonstrates that significantly faster than real time simulation is possible in all cases. Furthermore, with systematic replacement of the algebraic states with feedforward maps in the reduced order models, further computational savings of up to one order of magnitude can be achieved. This combination of model fidelity and computational tractability suggest suggests that the resulting reduced order models may be suitable for use in model based control of cogeneration plants.

scholarly journals Reduced-Order Models for Representing Converters in Power System Studies

2018 ◽  
Vol 33 (4) ◽  
pp. 3644-3654 ◽  
Author(s):  
Yunjie Gu ◽  
Nathaniel Bottrell ◽  
Timothy C. Green
Keyword(s):  
Power System ◽  
Reduced Order Models ◽  
Reduced Order

Model Reduction for Nonlinear Structural Systems Using Balanced Realization Theory

2013 ◽  
Author(s):  
Al Ferri
Keyword(s):  
Model Reduction ◽  
Dry Friction ◽  
Numerical Models ◽  
Contact Stiffness ◽  
Reduced Order Models ◽  
Joint Models ◽  
Reduced Order ◽  
Truncation Techniques ◽  
Modal Truncation

The development of accurate and efficient numerical models for jointed structures is an important and challenging problem. Due to nonlinearities in the joints, notably dry friction, contact stiffness, and impact, joint models are often complicated and computer-intensive. To create practical models, engineers typically combine “lumped joint models” with reduced-order models for the structural members that they connect. However, the model reduction often distorts how the joint behaves and sometimes destroys important qualitative traits. Simple modal truncation is often inadequate to produce reduced-order models because nonlinearities within the joints such as impact and dry friction can depend critically on the high-frequency characteristics of the mating structural elements. This paper examines the issues surrounding the development of accurate, reduced-order models for nonlinear, jointed structures. The concept of “balanced realizations” from control theory are used to create reduced-order models that best capture the input-output characterization of the linear substructures with the smallest model order. The balanced-realizations are seen to produce very favorable results when compared with standard modal truncation techniques.

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