On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition

Harold R.  Chamorro; A.-J.  Guel-Cortez; Camilo A.  Ordonez; Mario R.  Arrieta Paternina; Marko  Budisić

doi:10.1109/GreenTech48523.2021.00081

On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition

Harold R. Chamorro, A.-J. Guel-Cortez, Camilo A. Ordonez, Mario R. Arrieta Paternina, Marko Budisić

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

4 Citations (Scopus)

Abstract

Nowadays, power systems complexity requires of innovative methods to monitor and provide an adequate online assessment. Coherency identification (based on data-driven methods) is a potential tool that can be integrated into the system infrastructure for the protection and resilience of the power grid. This work presents a modification of the Koopman Mode Decomposition (KMD) by adding a sliding-window to emulate the processed system's signals and to visualise the data concentration as a Transmission System Operator (TSO). Finally, we present a study of a data-set of rotor angle observables from the Nordic 32 test system after a disturbance to observe the rapid coherency at specific time-shots. This study provides evidence that the proposed modified KMD is a fast and robust approach to analyze large time-domain simulation data.

Original language	English
Title of host publication	Proceedings - 2021 13th Annual IEEE Green Technologies Conference, GREENTECH 2021
Publisher	IEEE
Pages	484-488
Number of pages	5
ISBN (Electronic)	978-1-7281-9139-3
ISBN (Print)	978-1-7281-9140-9
DOIs	https://doi.org/10.1109/GreenTech48523.2021.00081
Publication status	Published - Apr 2021
Event	13th Annual IEEE Green Technologies (GreenTech) Conference - Online, Denver, United States Duration: 7 Apr 2021 → 9 Apr 2021 Conference number: 13

Publication series

Name	IEEE Green Technologies Conference
Volume	2021-April
ISSN (Electronic)	2166-5478

Conference

Conference	13th Annual IEEE Green Technologies (GreenTech) Conference
Country/Territory	United States
City	Denver
Period	7/04/21 → 9/04/21

Keywords

Koopman Mode Decomposition
On-line Identification
Power Systems Coherency
Rapid Coherency
Sliding-Window
Wide-Area Measurement Systems

ASJC Scopus subject areas

Electrical and Electronic Engineering
Ecological Modelling
Environmental Engineering

Access to Document

10.1109/GreenTech48523.2021.00081

Cite this

Chamorro, H. R., Guel-Cortez, A.-J., Ordonez, C. A., Arrieta Paternina, M. R., & Budisić, M. (2021). On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition. In Proceedings - 2021 13th Annual IEEE Green Technologies Conference, GREENTECH 2021 (pp. 484-488). Article 9458536 (IEEE Green Technologies Conference; Vol. 2021-April). IEEE. https://doi.org/10.1109/GreenTech48523.2021.00081

On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition. / Chamorro, Harold R.; Guel-Cortez, A.-J. ; Ordonez, Camilo A. et al.
Proceedings - 2021 13th Annual IEEE Green Technologies Conference, GREENTECH 2021. IEEE, 2021. p. 484-488 9458536 (IEEE Green Technologies Conference; Vol. 2021-April).

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

Chamorro, HR, Guel-Cortez, A-J, Ordonez, CA, Arrieta Paternina, MR & Budisić, M 2021, On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition. in Proceedings - 2021 13th Annual IEEE Green Technologies Conference, GREENTECH 2021., 9458536, IEEE Green Technologies Conference, vol. 2021-April, IEEE, pp. 484-488, 13th Annual IEEE Green Technologies (GreenTech) Conference, Denver, United States, 7/04/21. https://doi.org/10.1109/GreenTech48523.2021.00081

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abstract = "Nowadays, power systems complexity requires of innovative methods to monitor and provide an adequate online assessment. Coherency identification (based on data-driven methods) is a potential tool that can be integrated into the system infrastructure for the protection and resilience of the power grid. This work presents a modification of the Koopman Mode Decomposition (KMD) by adding a sliding-window to emulate the processed system's signals and to visualise the data concentration as a Transmission System Operator (TSO). Finally, we present a study of a data-set of rotor angle observables from the Nordic 32 test system after a disturbance to observe the rapid coherency at specific time-shots. This study provides evidence that the proposed modified KMD is a fast and robust approach to analyze large time-domain simulation data.",

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AB - Nowadays, power systems complexity requires of innovative methods to monitor and provide an adequate online assessment. Coherency identification (based on data-driven methods) is a potential tool that can be integrated into the system infrastructure for the protection and resilience of the power grid. This work presents a modification of the Koopman Mode Decomposition (KMD) by adding a sliding-window to emulate the processed system's signals and to visualise the data concentration as a Transmission System Operator (TSO). Finally, we present a study of a data-set of rotor angle observables from the Nordic 32 test system after a disturbance to observe the rapid coherency at specific time-shots. This study provides evidence that the proposed modified KMD is a fast and robust approach to analyze large time-domain simulation data.

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On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition

Abstract

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Keywords

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