A data-driven wind farm subsynchronous oscillation dynamic monitoring method and system

By using a data-driven approach, combining singular spectrum analysis, variational mode decomposition, and the Prony method, an assessment model for the energy influencing factors of subsynchronous oscillations in wind farms was established. This solved the problem of accurate identification and stability assessment of subsynchronous oscillations in wind farms, and enabled efficient monitoring and assessment of wind farm grid-connected systems.

CN122371138APending Publication Date: 2026-07-10STATE GRID JIANGSU ELECTRIC POWER CO LTD NANTONG POWER SUPPLY BRANCH +1
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Patent Information

Application Number
CN202610821997.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-09
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately identify and assess subsynchronous oscillation (SSO) incidents in wind farms, leading to difficulties in grid stability assessment. Furthermore, traditional analysis methods are ineffective in complex large-scale power grids.

Method used

Using a data-driven approach, we extracted the oscillation mode parameters of the wind farm grid-connected system through singular spectral analysis (SSA) and improved variational mode decomposition (VMD) combined with the Prony method. We then established an evaluation model for the influencing factors of oscillation energy by combining partial least squares regression and improved analytic hierarchy process.

Benefits of technology

It enables accurate dynamic monitoring and stability assessment of subsynchronous oscillations in wind farms, improves the accuracy and sensitivity of oscillation detection, and can quickly identify multimodal, nonlinear, and time-varying oscillation characteristics, providing reliable stability assessment.

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Abstract

This invention relates to the field of novel power system stability, and discloses a data-driven dynamic monitoring method and system for subsynchronous oscillations in wind farms. The method includes: analyzing system stability characteristics from an energy perspective and defining characteristic quantities that can quantify the oscillation stability level of the wind farm grid-connected system; employing a singular spectrum analysis algorithm to improve the adaptive variational mode decomposition method, accurately extracting the time-frequency signals of the oscillation modes, and achieving rapid identification of oscillation stability; and applying a comprehensive subjective and objective evaluation method to establish an evaluation model and quantitatively assess the impact of relevant influencing factors on the energy characteristics of the dominant subsynchronous oscillation mode. The quantitative assessment method for subsynchronous oscillation stability proposed in this invention is highly practical, capable of assessing system stability and analyzing the characteristics of the dominant oscillation mode using only measurement data. It provides guidance for the quantitative assessment of subsynchronous oscillation stability, disturbance location, and oscillation suppression in practical engineering projects.
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