Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents

Zhihao Jiang; Xuemeng Zhang; Yaosuo Xue; Alfonso G. Tarditi; Yilu Liu

doi:10.1109/PESGM40551.2019.8974099

Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents

Zhihao Jiang, Xuemeng Zhang, Yaosuo Xue, Alfonso G. Tarditi, Yilu Liu

Grid Systems Modeling and Controls

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The increasing complexity of power system has made it difficult to simulate large-scale power system in detail. Therefore, to improve computational efficiency, model reduction techniques has been applied to reduce the external area and focus on the dynamics of the internal area. This paper proposes a measurement-based model reduction method which reduces the external system by replacing external system with ARX equivalents. The modeled transfer function parameters are obtained using system identification approach. Case studies on the NPCC system and EI system are carried out. Results show that the proposed reduction method can effectively retain the dynamic behavior of the study area while mitigating computation burden.

Original language	English
Title of host publication	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Publisher	IEEE Computer Society
ISBN (Electronic)	9781728119816
DOIs	https://doi.org/10.1109/PESGM40551.2019.8974099
State	Published - Aug 2019
Event	2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States Duration: Aug 4 2019 → Aug 8 2019

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2019-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Country/Territory	United States
City	Atlanta
Period	08/4/19 → 08/8/19

Funding

This manuscript has been authored in part by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The US Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

ARX model
Dynamic equivalent
model reduction
power system dynamic simulation
system identification
transfer function

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10.1109/PESGM40551.2019.8974099

Cite this

@inproceedings{957ed687f2b343d4990686c24a7c3628,

title = "Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents",

abstract = "The increasing complexity of power system has made it difficult to simulate large-scale power system in detail. Therefore, to improve computational efficiency, model reduction techniques has been applied to reduce the external area and focus on the dynamics of the internal area. This paper proposes a measurement-based model reduction method which reduces the external system by replacing external system with ARX equivalents. The modeled transfer function parameters are obtained using system identification approach. Case studies on the NPCC system and EI system are carried out. Results show that the proposed reduction method can effectively retain the dynamic behavior of the study area while mitigating computation burden.",

keywords = "ARX model, Dynamic equivalent, model reduction, power system dynamic simulation, system identification, transfer function",

author = "Zhihao Jiang and Xuemeng Zhang and Yaosuo Xue and Tarditi, {Alfonso G.} and Yilu Liu",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Power and Energy Society General Meeting, PESGM 2019 ; Conference date: 04-08-2019 Through 08-08-2019",

year = "2019",

month = aug,

doi = "10.1109/PESGM40551.2019.8974099",

language = "English",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2019 IEEE Power and Energy Society General Meeting, PESGM 2019",

}

Jiang, Z, Zhang, X, Xue, Y, Tarditi, AG & Liu, Y 2019, Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents. in 2019 IEEE Power and Energy Society General Meeting, PESGM 2019., 8974099, IEEE Power and Energy Society General Meeting, vol. 2019-August, IEEE Computer Society, 2019 IEEE Power and Energy Society General Meeting, PESGM 2019, Atlanta, United States, 08/4/19. https://doi.org/10.1109/PESGM40551.2019.8974099

Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents. / Jiang, Zhihao; Zhang, Xuemeng; Xue, Yaosuo et al.
2019 IEEE Power and Energy Society General Meeting, PESGM 2019. IEEE Computer Society, 2019. 8974099 (IEEE Power and Energy Society General Meeting; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents

AU - Jiang, Zhihao

AU - Zhang, Xuemeng

AU - Xue, Yaosuo

AU - Tarditi, Alfonso G.

AU - Liu, Yilu

PY - 2019/8

Y1 - 2019/8

N2 - The increasing complexity of power system has made it difficult to simulate large-scale power system in detail. Therefore, to improve computational efficiency, model reduction techniques has been applied to reduce the external area and focus on the dynamics of the internal area. This paper proposes a measurement-based model reduction method which reduces the external system by replacing external system with ARX equivalents. The modeled transfer function parameters are obtained using system identification approach. Case studies on the NPCC system and EI system are carried out. Results show that the proposed reduction method can effectively retain the dynamic behavior of the study area while mitigating computation burden.

AB - The increasing complexity of power system has made it difficult to simulate large-scale power system in detail. Therefore, to improve computational efficiency, model reduction techniques has been applied to reduce the external area and focus on the dynamics of the internal area. This paper proposes a measurement-based model reduction method which reduces the external system by replacing external system with ARX equivalents. The modeled transfer function parameters are obtained using system identification approach. Case studies on the NPCC system and EI system are carried out. Results show that the proposed reduction method can effectively retain the dynamic behavior of the study area while mitigating computation burden.

KW - ARX model

KW - Dynamic equivalent

KW - model reduction

KW - power system dynamic simulation

KW - system identification

KW - transfer function

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U2 - 10.1109/PESGM40551.2019.8974099

DO - 10.1109/PESGM40551.2019.8974099

M3 - Conference contribution

AN - SCOPUS:85079066023

T3 - IEEE Power and Energy Society General Meeting

BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

PB - IEEE Computer Society

T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

Y2 - 4 August 2019 through 8 August 2019

ER -

Measurement-based Power System Dynamic Model Reduction Using ARX Equivalents

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