Adaptive Maximum Power Control Based on Optimum Torque Method for Wind Turbine by Using Fuzzy-Logic Adaption Mechanisms during Partial Load Operation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper aims to increase the effectiveness of the Maximum Power Control (MPC) strategy by using a new Adaptive Maximum Power Control method (AMPC) for maximizing the power delivered by the Wind Turbine System (WTS) during partial load operation whatever the disturbances caused by variations in wind profile. The AMPC is applied to one of the frequently used Maximum Power Point Tracking (MPPT) methods called as Optimum Torque (OT) MPPT algorithm. Furthermore, the proposed AMPC strategy aims to optimize the wind energy captured by the WTS during partial load operation under rating wind speed, using Fuzzy-Logic as Adaption Mechanisms (AMPC- FLC). Additionally, the performances of the proposed improved OT-MPPT method based on AMPC-FLC are compared to the OT-MPPT method based on Conventional Maximum Power Control (CMPC-PI) under the same conditions. The robustness, dynamic performance, and fast approximation of the optimal value are proved with the numerical simulations under MATLAB/Simulink® software.
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.
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 | 0.001 |
| 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) | 0.000 | 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 it