An LQR Controller for Damping of Subsynchronous Interaction in DFIG-Based Wind Farms
Bibliographic record
Abstract
This paper presents a linear-quadratic regulator (LQR) for damping of subsynchronous interaction (SSI) in doubly-fed induction generator (DFIG)-based wind farms. The proposed LQR controller employs a full-state observer to estimate all state variables. The output of the LQR is added to control signals of inner current control loops of DFIG converters as supplementary control signals. The supplementary control signals are dynamically limited to avoid saturating the converters and to provide the DFIG with the desired transient response against power system faults. The proposed SSI damping controller is designed for a realistic series compensated wind farm, and its performance is verified using electromagnetic transient (EMT) simulations. The EMT simulations are performed using a detailed DFIG model which includes all nonlinearities and all required transient functions to meet the grid code requirements corresponding to fault-ride-through (FRT). The results show that the proposed SSI controller is able to significantly mitigate the oscillations due to the SSI phenomenon, and to provide excellent transient response against systems faults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".