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Energies
Volume 18
Issue 11
10.3390/en18112693
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm

by
José Oscullo Lala
1,
Nathaly Orozco Garzón
2,*,
Henry Carvajal Mora
2,
Diego Echeverria
1,
José Vega-Sánchez
3 and
Takaaki Ohishi
4
1
Department of Energy, National Polytechnic School, Quito 170525, Ecuador
2
Faculty of Engineering and Applied Sciences, Networking and Telecommunications Engineering, ETEL Research Group, Universidad de Las Américas (UDLA), Quito 170503, Ecuador
3
Colegio de Ciencias e Ingenierías “El Politécnico”, Universidad San Francisco de Quito (USFQ), Diego de Robles S/N, Quito 170157, Ecuador
4
School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas 13083-852, SP, Brazil
*
Author to whom correspondence should be addressed.
Energies 2025, 18(11), 2693; https://doi.org/10.3390/en18112693
Submission received: 15 April 2025 / Revised: 9 May 2025 / Accepted: 20 May 2025 / Published: 22 May 2025
(This article belongs to the Section F1: Electrical Power System)
Versions Notes

Abstract

The growing complexity and uncertainty in modern power systems—driven by increased integration of renewable energy sources and variable loads—underscore the need for robust tools to assess dynamic stability. This paper presents an enhanced methodology for modal analysis that combines Adaptive Variational Mode Decomposition (A-VMD) with Prony’s method. A novel energy-based selection mechanism is introduced to determine the optimal number of intrinsic mode functions (IMFs), improving the decomposition’s adaptability and precision. The resulting modes are analyzed to estimate modal frequencies and damping ratios. Validation is conducted using both synthetic datasets and real synchrophasor measurements from Ecuador’s national power grid under ambient and disturbed operating conditions. The proposed approach is benchmarked against established techniques, including a matrix pencil, conventional VMD-Prony, and commercial tools such as WAProtector and DIgSILENT PowerFactory. The results demonstrate that A-VMD consistently delivers more accurate and robust performance, especially for low signal-to-noise ratios and low-energy ambient conditions. These findings highlight the method’s potential for real-time oscillation mode identification and small-signal stability monitoring in wide-area power systems.
Keywords: electromechanical modes; power system stability; wide-area measurement systems; signal decomposition; variational mode decomposition electromechanical modes; power system stability; wide-area measurement systems; signal decomposition; variational mode decomposition

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MDPI and ACS Style

Oscullo Lala, J.; Orozco Garzón, N.; Carvajal Mora, H.; Echeverria, D.; Vega-Sánchez, J.; Ohishi, T. Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm. Energies 2025, 18, 2693. https://doi.org/10.3390/en18112693

AMA Style

Oscullo Lala J, Orozco Garzón N, Carvajal Mora H, Echeverria D, Vega-Sánchez J, Ohishi T. Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm. Energies. 2025; 18(11):2693. https://doi.org/10.3390/en18112693

Chicago/Turabian Style

Oscullo Lala, José, Nathaly Orozco Garzón, Henry Carvajal Mora, Diego Echeverria, José Vega-Sánchez, and Takaaki Ohishi. 2025. "Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm" Energies 18, no. 11: 2693. https://doi.org/10.3390/en18112693

APA Style

Oscullo Lala, J., Orozco Garzón, N., Carvajal Mora, H., Echeverria, D., Vega-Sánchez, J., & Ohishi, T. (2025). Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm. Energies, 18(11), 2693. https://doi.org/10.3390/en18112693

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