Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification

Paul Frutos; Juan Manuel Guerrero; Iker Muniategui; Iban Vicente; Aitor Endemano; Fernando Briz

doi:10.1109/ECCE47101.2021.9595947

Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification

Paul Frutos
, Juan Manuel Guerrero
, Iker Muniategui
, Iban Vicente
, Aitor Endemano
, Fernando Briz

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

6 Citations (Scopus)

Abstract

Dynamic interactions among AC railway networks and train power converters have been reported to cause low-frequency oscillations (LFO) and eventually instability phenomena, which can collapse the railway power system. Several system parameters can influence the appearance of LFO, including catenary line length, power consumption, control bandwidths, etc. This paper proposes a methodology for the analysis and understanding of the impact of all these parameters on the LFO. The proposed method combines time-domain simulations with eigenvalue analysis. Eigenvalue migration will be shown to be a powerful tool to understand the risk of instability and to analyse potential remedial actions.

Original language	English
Title of host publication	2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1573-1579
Number of pages	7
ISBN (Electronic)	9781728151359
DOIs	https://doi.org/10.1109/ECCE47101.2021.9595947
Publication status	Published - 2021
Externally published	Yes
Event	13th IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Virtual, Online, Canada Duration: 10 Oct 2021 → 14 Oct 2021

Publication series

Name	2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings

Conference

Conference	13th IEEE Energy Conversion Congress and Exposition, ECCE 2021
Country/Territory	Canada
City	Virtual, Online
Period	10/10/21 → 14/10/21

Access to Document

10.1109/ECCE47101.2021.9595947

Cite this

Frutos, P., Guerrero, J. M., Muniategui, I., Vicente, I., Endemano, A., & Briz, F. (2021). Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification. In 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings (pp. 1573-1579). (2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE47101.2021.9595947

Frutos, Paul ; Guerrero, Juan Manuel ; Muniategui, Iker et al. / Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification. 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 1573-1579 (2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings).

@inproceedings{d894ace45f5943fba064eb9c86469e56,

title = "Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification",

abstract = "Dynamic interactions among AC railway networks and train power converters have been reported to cause low-frequency oscillations (LFO) and eventually instability phenomena, which can collapse the railway power system. Several system parameters can influence the appearance of LFO, including catenary line length, power consumption, control bandwidths, etc. This paper proposes a methodology for the analysis and understanding of the impact of all these parameters on the LFO. The proposed method combines time-domain simulations with eigenvalue analysis. Eigenvalue migration will be shown to be a powerful tool to understand the risk of instability and to analyse potential remedial actions.",

author = "Paul Frutos and Guerrero, \{Juan Manuel\} and Iker Muniategui and Iban Vicente and Aitor Endemano and Fernando Briz",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 13th IEEE Energy Conversion Congress and Exposition, ECCE 2021 ; Conference date: 10-10-2021 Through 14-10-2021",

year = "2021",

doi = "10.1109/ECCE47101.2021.9595947",

language = "English",

series = "2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1573--1579",

booktitle = "2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings",

address = "United States",

}

Frutos, P, Guerrero, JM, Muniategui, I, Vicente, I, Endemano, A & Briz, F 2021, Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification. in 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings. 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1573-1579, 13th IEEE Energy Conversion Congress and Exposition, ECCE 2021, Virtual, Online, Canada, 10/10/21. https://doi.org/10.1109/ECCE47101.2021.9595947

Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification. / Frutos, Paul; Guerrero, Juan Manuel; Muniategui, Iker et al.
2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1573-1579 (2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings).

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

TY - GEN

T1 - Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification

AU - Frutos, Paul

AU - Guerrero, Juan Manuel

AU - Muniategui, Iker

AU - Vicente, Iban

AU - Endemano, Aitor

AU - Briz, Fernando

PY - 2021

Y1 - 2021

N2 - Dynamic interactions among AC railway networks and train power converters have been reported to cause low-frequency oscillations (LFO) and eventually instability phenomena, which can collapse the railway power system. Several system parameters can influence the appearance of LFO, including catenary line length, power consumption, control bandwidths, etc. This paper proposes a methodology for the analysis and understanding of the impact of all these parameters on the LFO. The proposed method combines time-domain simulations with eigenvalue analysis. Eigenvalue migration will be shown to be a powerful tool to understand the risk of instability and to analyse potential remedial actions.

AB - Dynamic interactions among AC railway networks and train power converters have been reported to cause low-frequency oscillations (LFO) and eventually instability phenomena, which can collapse the railway power system. Several system parameters can influence the appearance of LFO, including catenary line length, power consumption, control bandwidths, etc. This paper proposes a methodology for the analysis and understanding of the impact of all these parameters on the LFO. The proposed method combines time-domain simulations with eigenvalue analysis. Eigenvalue migration will be shown to be a powerful tool to understand the risk of instability and to analyse potential remedial actions.

UR - https://www.scopus.com/pages/publications/85123351571

U2 - 10.1109/ECCE47101.2021.9595947

DO - 10.1109/ECCE47101.2021.9595947

M3 - Conference contribution

AN - SCOPUS:85123351571

T3 - 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings

SP - 1573

EP - 1579

BT - 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 13th IEEE Energy Conversion Congress and Exposition, ECCE 2021

Y2 - 10 October 2021 through 14 October 2021

ER -

Frutos P, Guerrero JM, Muniategui I, Vicente I, Endemano A, Briz F. Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification. In 2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 1573-1579. (2021 IEEE Energy Conversion Congress and Exposition, ECCE 2021 - Proceedings). doi: 10.1109/ECCE47101.2021.9595947

Low-Frequency Oscillations Analysis in AC Railway Networks Using Eigenmode Identification

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