Using a combination of four different strategies to increase the quality of current and power produced by multi-rotor wind turbine systems
Bibliographic record
Abstract
Using conventional controls often leads to undesirable results in the power and current quality of wind-based energy systems. To overcome the problem of low power/current quality, a combination of control strategies is an effective and convenient solution. In this study, it was proposed to combine the proportional-derivative regulator, proportional-integral regulator, super-twisting control, and fractional calculus to obtain a new controller characterized by high durability and distinctive performance. This proposed controller replaces traditional controllers for indirect fielded-oriented control of a doubly-fed induction generator. In this proposed approach, the pulse width modulation strategy was used to control the operation of the machine inverter. The proposed approach increases performance, and durability, and improves dynamic response to power. The proposed approach was used to control the generator inverter only to show how effective and efficient it is in improving the quality of power and current without resorting to controlling the grid inverter. This proposed strategy was implemented using MATLAB, where the effectiveness of the control strategy is evaluated under variable wind conditions and parameter changes, with the results compared to the traditional approach and some related work. The comparison with the conventional approach shows that the proposed approach reduces the total harmonic distortion of current by 97.24% and 91.81%. The simulation results show that the proposed approach significantly outperforms traditional control in terms of power and current quality, as active power ripples were reduced by 99.98% and 89.93%, current ripples were reduced by 99.74% and 99.38%, and reactive power ripples were reduced by 99.97% and 60.85%. Also, the proposed approach improves the steady-state error value by 96.85% and 99.98% for active power and by 67.55% and 96.59% for reactive power. These reduction ratios highlight the superiority and effectiveness of the proposed approach in improving the properties of the studied energy system, which makes it of interest in other industrial applications.
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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 | 0.001 | 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) | 0.000 | 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 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".