Performance Improvement of Doubly Fed Induction Generator-based Wind Energy Conversion System during Various Internal Converter Faults
Bibliographic record
Abstract
The doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) currently dominates the wind energy market due to its advantages over other WECSs. In it, the rotor is interfaced with the AC network through a rotor side voltage source converter (RSC) and a grid side voltage source converter (GSC) which are coupled with a DC-link capacitor that helps to maintain the voltage at the point of common coupling within permissible limits. A DFIG's sensitivity to external faults has motivated researchers to investigate the impacts of various grid disturbances, such as voltage sag, voltage swell and short-circuit faults, on the grid side of its low-voltage ride-through (LVRT) capability. However, no attention has been paid to examining the impacts of RSC and GSC internal faults on the LVRT capability of a DFIG-based WECS. This thesis investigates a new DFIG problem that may frequently occur and proposes a solution to it. In this study, the impacts of various intermittent and sustained internal GSC and RSC faults on the overall performance of a DFIG-based WECS are compared. These faults include a fire-through, misfire, flashover and short circuit across the DC-link capacitor that can be caused by various malfunctions in the control and firing equipment of the converter station. In this context, the effects of the previously mentioned faults on various variables of the DFIG-based WECS are investigated using PSCAD/EMTDC software package. Compliance of the DFIG performance under such faults with the recent LVRT grid codes of the USA, Spain, Mexico, Denmark, Ireland, Germany, Quebec and the UK are also investigated. Two proposed solutions to these problems are introduced; a conventional STATCOM; and a STATCOM with the application of a high temperature superconducting (HTS) coil. The key objectives of the proposed solutions are to improve the LVRT capability of the DFIG and maintain its unity power factor operation during various voltage source converter (VSC) faults. To introduce a general and robust controller that helps to enhance the system’s performance under various faults, the controller parameters are tuned using the Nelder and Mead optimisation technique. This study determines that the effect of internal VSC faults should be considered in the design of a DFIG control system and reactive power compensation must be available to enable the wind turbine to comply with the stringent LVRT specifications enforced by international grid codes. Moreover, a reliable technique for monitoring conditions is necessary to detect these faults in advance in order to prevent their severe consequences.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".