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

José Oscullo Lala, Nathaly Orozco Garzón (), Henry Carvajal Mora, Diego Echeverria, José Vega-Sánchez and Takaaki Ohishi
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José Oscullo Lala: Department of Energy, National Polytechnic School, Quito 170525, Ecuador
Nathaly Orozco Garzón: ETEL Research Group, Faculty of Engineering and Applied Sciences, Networking and Telecommunications Engineering, Universidad de Las Américas (UDLA), Quito 170503, Ecuador
Henry Carvajal Mora: ETEL Research Group, Faculty of Engineering and Applied Sciences, Networking and Telecommunications Engineering, Universidad de Las Américas (UDLA), Quito 170503, Ecuador
Diego Echeverria: Department of Energy, National Polytechnic School, Quito 170525, Ecuador
José Vega-Sánchez: Colegio de Ciencias e Ingenierías “El Politécnico”, Universidad San Francisco de Quito (USFQ), Diego de Robles S/N, Quito 170157, Ecuador
Takaaki Ohishi: School of Electrical and Computer Engineering, University of Campinas (UNICAMP), Campinas 13083-852, SP, Brazil

Energies, 2025, vol. 18, issue 11, 1-21

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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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