Effects of nonlinear efficiency characteristics on the power-tracking control: a case study of hydrokinetic energy conversion system
Bibliographic record
Abstract
Maximum power point tracking (MPPT) for many alternative energy conversion systems implies the application of control methods where the operation of the primary energy conversion process is optimized through a nonlinear control arrangement. This assumes the presence of constant efficiency values for the subsystems in cascade to the front-end process. In case, efficiency of the subsequent stages are not constant and are dependent on diverse operating conditions, it becomes important to identify the success of power tracking as seen by the load unit. In this work hydrokinetic energy conversion systems are studied in this regard. A repetitive approach that matches nonlinear efficiency information to the overall performance of the system is presented. With specific focus on `power curve' and `performance/efficiency curve' two figures of merit are introduced to identify issues such as success of power tracking and divergence from optimum operating point. A comprehensive simulation study and a experimental test example are also presented. This method can also be used for identifying the effects on efficiency nonlinearity in other alternative energy systems.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".