A doubly-fed induction machine and energy storage system for wind power generation
Bibliographic record
Abstract
Wind power has become a very important source of renewable energy, and has been shown to complement central generation effectively. However, good power quality from distributed generators is vital, and hence independent control of the real and reactive power is desirable. Also, there has been an increasing demand for alternative energy sources to behave like conventional generators, whereby their output power is deterministic. Wind energy is an inherently stochastic system and, therefore, external measures must be used to overcome the fluctuations in the generator's energy production. The paper deals with the modeling and simulation of a doubly-fed induction machine as a wind power generator. The ability of the system to provide independent control of the real and reactive power is demonstrated. The incorporation of a battery or other energy storage device in the DC link enables temporary storage of energy and, therefore, the ability to provide smooth output power which is both deterministic and resistant to wind speed fluctuations. Power electronic converters directly control the machine and act as the interface between the storage system and the grid. This allows full control over voltage characteristics as well as real power generation. Simulations of the system in EMTP-RV show that the design is feasible.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".