Dynamic-Tracking Damping Controller for DFIG-Based Wind Farms to Mitigate Sub-Synchronous Control Interactions
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Bibliographic record
Abstract
This paper proposes a dynamic-tracking damping controller (DTDC) and designs an implementation scheme to alleviate the sub-synchronous control interactions (SSCI) in series-compensated networks integrated with doubly-fed induction generator (DFIG)-based wind farms. The DTDC can track sub-synchronous oscillatory current components under various operating conditions, providing high damping performance for DFIG wind turbines at a broader range of sub-synchronous frequencies. This is accomplished by designing an extra extended state observer (ESO)-based compensated loop for the rotor-side converter of DFIG, which enables the extraction and compensation of oscillatory current components at the sub-synchronous frequencies. In addition, the implementation scheme for the damping controller is designed based on the dissipated energy criterion, which can identify the weak damping wind farm and determine the number of wind turbines required to be installed. The proposed DTDC's effectiveness and implementation scheme are validated using the modified IEEE first benchmark model and a wind farm model in North China, respectively. The control hardware-in-loop (CHIL) experiments results demonstrate that the DTDC outperforms traditional approaches with superior damping and robustness under varying wind speeds, compensation levels, and the number of online wind turbines.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it