Open-loop maximum power point tracking strategy for Marine Current Turbines based on resource prediction
Bibliographic record
Abstract
This paper presents the theory for a model-based Maximum Power Point Tracking (MPPTs) strategy for Marine Current Turbines (MCTs) that computes the optimal operating point using resource prediction and a look-up table. The high predictability of the Marine Currents (MCs) is exploited in order to produce a simple algorithm that calculates offline the optimal operating point for an evolving date and time. This eliminates the use of sensors to measure the current or the use of a perturbation to scan the curve. Two MPPT methods based on this strategy are discussed in detail: 1) fixed rotating speed with variable pitch angle and 2) fixed pitch angle with variable rotating speed. As a result, the two proposed MPPT methods improve the efficiency of the MCT creating a sensor-less, open loop strategy with precision and simplicity. The information needed to predict the MC is obtained through site characterization, a process required for any investment in green energy. The effectiveness of the proposed strategy is demonstrated through simulations.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".