Reliability Evaluation of a Tidal Power Generation System Considering Tidal Current Speeds
Bibliographic record
Abstract
This paper presents a reliability evaluation method for a tidal power generation system (TPGS) with a doubly-fed induction generator (DFIG). The key to the method is the modeling of the tidal current speed-dependent failure rates of the rotor side converter (RSC) and grid side converter (GSC). The models for calculating the rotor currents through the RSC and GSC and the rotor current state related failure rates are presented. Based on the Wakeby distribution of tidal current speed, a multistate discrete probability distribution technique for rotor current is developed. Case studies are described using tidal current speed data from four coastal sites in North America. The results indicate that the failure rates of the RSC, GSC, and the entire TPGS vary with tidal current speeds and the probability distributions of tidal current speed. The TPGS suffers a much higher failure risk in the super-synchronous mode than in the idle and subsynchronous modes. The failure rate of the RSC is much higher than that of the GSC. The change trends in the failure rates of RSC and GSC in the operation modes are different. The probability distributions of tidal current speed have significant impacts on the reliability of the TPGS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".