Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Lingling Fan; Zhixin Miao; Shahil Shah; Przemyslaw Koralewicz; Vahan Gevorgian; Jian Fu

doi:10.1109/MPE.2022.3150827

Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Lingling Fan
, Zhixin Miao
, Shahil Shah
, Przemyslaw Koralewicz
, Vahan Gevorgian
, Jian Fu

University of South Florida
United States Department of Energy

Research output: Contribution to journal › Article › peer-review

52 Scopus Citations

Abstract

This article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time.

Original language	American English
Pages (from-to)	64-76
Number of pages	13
Journal	IEEE Power and Energy Magazine
Volume	20
Issue number	3
DOIs	https://doi.org/10.1109/MPE.2022.3150827 https://doi.org/10.1109/MPE.2022.3150827
State	Published - 2022

Bibliographical note

Publisher Copyright:
© 2003-2012 IEEE.

NLR Publication Number

NREL/JA-5D00-80444

Keywords

black-box models
control interactions
dynamic modeling
frequency-domain modeling
impedance response
measurement-based modeling
resonance
stability

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Cite this

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title = "Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling",

abstract = "This article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time.",

keywords = "black-box models, control interactions, dynamic modeling, frequency-domain modeling, impedance response, measurement-based modeling, resonance, stability",

author = "Lingling Fan and Zhixin Miao and Shahil Shah and Przemyslaw Koralewicz and Vahan Gevorgian and Jian Fu",

note = "Publisher Copyright: {\textcopyright} 2003-2012 IEEE.",

year = "2022",

doi = "10.1109/MPE.2022.3150827",

language = "American English",

volume = "20",

pages = "64--76",

journal = "IEEE Power and Energy Magazine",

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T1 - Data-Driven Dynamic Modeling in Power Systems

T2 - A Fresh Look on Inverter-Based Resource Modeling

AU - Fan, Lingling

AU - Miao, Zhixin

AU - Shah, Shahil

AU - Koralewicz, Przemyslaw

AU - Gevorgian, Vahan

AU - Fu, Jian

PY - 2022

Y1 - 2022

N2 - This article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time.

AB - This article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time.

KW - black-box models

KW - control interactions

KW - dynamic modeling

KW - frequency-domain modeling

KW - impedance response

KW - measurement-based modeling

KW - resonance

KW - stability

UR - https://www.scopus.com/pages/publications/85129265620

U2 - 10.1109/MPE.2022.3150827

DO - 10.1109/MPE.2022.3150827

M3 - Article

AN - SCOPUS:85129265620

SN - 1540-7977

VL - 20

SP - 64

EP - 76

JO - IEEE Power and Energy Magazine

JF - IEEE Power and Energy Magazine

IS - 3

ER -

Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Abstract

Bibliographical note

NLR Publication Number

Keywords

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