High-power wind energy conversion systems: State-of-the-art and emerging technologies
Bibliographic record
Abstract
This paper presents a comprehensive study on the state-of-the-art and emerging wind energy technologies from the electrical engineering perspective. In an attempt to decrease cost of energy, increase the wind energy conversion efficiency, reliability, power density, and comply with the stringent grid codes, the electric generators and power electronic converters have emerged in a rigorous manner. From the market based survey, the most successful generator-converter configurations are addressed along with few promising topologies available in the literature. The back-to-back connected converters, passive generator-side converters, converters for multiphase generators, and converters without intermediate dc-link are investigated for high-power wind energy conversion systems (WECS), and presented in low and medium voltage category. The onshore and offshore wind farm configurations are analyzed with respect to the series/parallel connection of wind turbine ac/dc output terminals, and high voltage ac/dc transmission. The fault-ride through compliance methods used in the induction and synchronous generator based WECS are also discussed. The past, present and future trends in megawatt WECS are reviewed in terms of mechanical and electrical technologies, integration to power systems, and control theory. The important survey results, and technical merits and demerits of various WECS electrical systems are summarized by tables. The list of current and future wind turbines are also provided along with technical details.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".