Coupling DFIG-Based Wind Turbines with the Grid under Voltage Imbalance Conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A smooth coupling is implemented between the grid and doubly fed induction generator-based wind turbines (DFIG-WTs) during grid voltage imbalance. The nonlinear characteristics of a grid-connected DFIG-WT system may increase stresses on the mechanical and electrical components of wind turbines. Such difficulties are greatly increased during periods of voltage imbalance. Consequently, in this paper, a new control scheme is proposed to regulate DFIGs in order to support a smooth connection to the grid during voltage imbalance. In synchronization mode, the positive sequence of the rotor dq-axes currents regulates the stator q-axis EMF that is to be synchronized with the q-axis voltage of the grid-side voltage. The phase difference between the grid and stator voltages is compensated by adjusting the stator d-axis EMF to zero. Under normal conditions, a PR controller is used to dampen the negative sequence of the rotor dq-axes currents. PI current controllers are tuned to control the positive sequence of the DFIG rotor currents, while PR current controllers are used to regulate the negative sequence of the rotor currents during synchronization and under normal operation conditions. Experiments are performed to verify the smooth synchronization of the DFIG and the robustness of the proposed control scheme during grid voltage imbalance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it