Low computational complexity model reduction of power systems with preservation of physical characteristics
File(s)
Published version
Author(s)
Scarciotti, G
Type
Journal Article
Abstract
A data-driven algorithm recently proposed to solve
the problem of model reduction by moment matching is extended
to multi-input, multi-output systems. The algorithm is
exploited for the model reduction of large-scale interconnected
power systems and it offers, simultaneously, a low computational
complexity approximation of the moments and the possibility
to easily enforce constraints on the reduced order model. This
advantage is used to preserve selected slow and poorly damped
modes. The preservation of these modes has been shown to be
important from a physical point of view and in obtaining an
overall good approximation. The problem of the choice of the socalled
tangential directions is also analyzed. The algorithm and
the resulting reduced order model are validated with the study
of the dynamic response of the NETS-NYPS benchmark system
(68-Bus, 16-Machine, 5-Area) to multiple fault scenarios.
the problem of model reduction by moment matching is extended
to multi-input, multi-output systems. The algorithm is
exploited for the model reduction of large-scale interconnected
power systems and it offers, simultaneously, a low computational
complexity approximation of the moments and the possibility
to easily enforce constraints on the reduced order model. This
advantage is used to preserve selected slow and poorly damped
modes. The preservation of these modes has been shown to be
important from a physical point of view and in obtaining an
overall good approximation. The problem of the choice of the socalled
tangential directions is also analyzed. The algorithm and
the resulting reduced order model are validated with the study
of the dynamic response of the NETS-NYPS benchmark system
(68-Bus, 16-Machine, 5-Area) to multiple fault scenarios.
Date Issued
2016-05-06
Date Acceptance
2016-04-16
Citation
IEEE Transactions on Power Systems, 2016, 32 (1), pp.743-752
ISSN
1558-0679
Publisher
IEEE
Start Page
743
End Page
752
Journal / Book Title
IEEE Transactions on Power Systems
Volume
32
Issue
1
Copyright Statement
© 2016 IEEE. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/.
License URL
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/G066477/1
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Coherency
dynamic equivalents
model reduction from data
model reduction of power systems
INTERPOLATION PROBLEM
LINEAR-SYSTEMS
CONTROLLABILITY
DECOMPOSITION
IDENTIFICATION
APPROXIMATIONS
OBSERVABILITY
AGGREGATION
EQUIVALENTS
FAMILIES
0906 Electrical And Electronic Engineering
Energy
Publication Status
Published