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Record W4402023623 · doi:10.1016/j.prime.2024.100749

Using the proportional dual integral strategy to improve the characteristics of the indirect field-oriented control of DFIG-based wind turbine systems

2024· article· en· W4402023623 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuee-Prime - Advances in Electrical Engineering Electronics and Energy · 2024
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsTurbineDoubly fed electric machineDual (grammatical number)Field (mathematics)Control theory (sociology)Wind powerControl (management)Environmental scienceEngineeringPhysicsComputer scienceAerospace engineeringMathematicsPower (physics)Electrical engineeringAC powerThermodynamics

Abstract

fetched live from OpenAlex

• Indirect FOC technique with PDI controllers prove a good performance for DFIG-based wind turbine systems. • PDI regulator shows more performances than PI regulator and hysteresis comparators. • Indirect FOC-PDI technique reduced the power ripples and improved robustness. • Indirect FOC-PDI technique reduced the THD value of current. In this work, a new indirect field-oriented command (IFOC) for wind systems based on a doubly-fed induction generator (DFIG) is designed to get better energy and stream quality. Also, overcoming the problems of IFOC. It is proposed to use proportional dual integral (PDI) controllers in order to replace traditional controllers and augment the robustness of the studied wind turbine system. The proposed IFOC-PDI is a modification of the IFOC, where the basic idea behind the designed technique is to combine a proportional-integral (PI) regulator with an integral term. This technique has been applied to the machine inverter, where the IFOC-PDI aims to calculate reference voltage values. The pulse width modulation (PWM) is used to translate voltage reference values ​​into pulses to run the machine inverter. The main objective of this article is to compare the competence of the IFOC-PDI to that of the IFOC-PI in different tests, including two different wind speed profiles and DFIG parameters variation. The major benefit of this command is a decrease in harmonic distortion of the currents, and active and reactive power ( Ps and Qs ) fluctuations. The results using MATLAB demonstrated that the IFOC-PDI improved the IFOC-PI in the minimization of stream harmonic distortion (6.63%, 10.42%, and 17.86%) and notable minimization of fluctuations in both Ps (32.08%, 46.24%, and 12.10%) and Qs (45.95%, 66.88%, and 14.49%). Also, the overshoot value of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 57.79%, 12.41%, and 33.96%. The steady-state error of Ps was minimized compared to the IFOC-PI in all tests by ratios estimated at 29.43%, 85.88%, and 76.36%. The IFOC-PDI is also very resistant in the case of DFIG parameters variation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.206
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it