Identification of Oscillations in Wind Farms by Performing Modal Analysis Using Eigensystem Realization Algorithm

In this study, we focus on the application of the eigensystem realization algorithm (ERA) for modal analysis in wind farms, specifically to identify the oscillations that could impact system performance and stability. The ERA is adept at determining the natural frequencies, damping ratios, and mode shapes of a dynamic system from measured response data. For our analysis, a model wind farm with three pairs of wind turbines that are connected to an electrical distribution system (EDS) is subjected to a simulated disturbance, and the resulting transient responses are recorded. Using ERA, we identify dominant modes and their corresponding properties, which are crucial for understanding the dynamics of the wind farm system. This method offers a systematic approach to analyze the wind turbines' responses to disturbances, providing valuable insights into each turbine's contribution to the overall system dynamics. This analysis is essential for designing control strategies aimed at mitigating the effects of forced oscillations, enhancing the stability and efficiency of wind power generation.

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Published
2025-05-23
DOI
https://doi.org/10.1109/apsit63993.2025.11086120
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Identification of Oscillations in Wind Farms by Performing Modal Analysis Using Eigensystem Realization Algorithm

Mayukha Pal, Pratyush Chakraborty, Prasanta K. Panigrahi, K. Victor Sam Moses Babu
Power Systems and Renewable Energy
article

Identification of Oscillations in Wind Farms by Performing Modal Analysis Using Eigensystem Realization Algorithm

Mayukha Pal, Pratyush Chakraborty, Prasanta K. Panigrahi, K. Victor Sam Moses Babu
article en

Abstract

In this study, we focus on the application of the eigensystem realization algorithm (ERA) for modal analysis in wind farms, specifically to identify the oscillations that could impact system performance and stability. The ERA is adept at determining the natural frequencies, damping ratios, and mode shapes of a dynamic system from measured response data. For our analysis, a model wind farm with three pairs of wind turbines that are connected to an electrical distribution system (EDS) is subjected to a simulated disturbance, and the resulting transient responses are recorded. Using ERA, we identify dominant modes and their corresponding properties, which are crucial for understanding the dynamics of the wind farm system. This method offers a systematic approach to analyze the wind turbines' responses to disturbances, providing valuable insights into each turbine's contribution to the overall system dynamics. This analysis is essential for designing control strategies aimed at mitigating the effects of forced oscillations, enhancing the stability and efficiency of wind power generation.

Siksha O Anusandhan University (IN), Birla Institute of Technology and Science - Hyderabad Campus (IN), ABB (India) (IN)
Affordable and clean energy
Openalex Percentile: Top 81%
Power Systems and Renewable Energy
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