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Record W3213050362

New control strategy for permanent magnet synchronous generator (PMSG) wind turbine

2020· article· it· W3213050362 on OpenAlexfundno aff
Seyed Mehdi Mozayan

Bibliographic record

VenueEspace École de technologie supérieure (École de technologie supérieure) · 2020
Typearticle
Languageit
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsnot available
FundersÉcole de technologie supérieure
KeywordsPermanent magnet synchronous generatorTurbineWind powerControl theory (sociology)EngineeringTotal harmonic distortionFault (geology)Rotor (electric)Power optimizerMaximum power point trackingComputer scienceInverterElectrical engineeringMagnetVoltageControl (management)Mechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Due to extensive research in the wind turbine community, advanced technologies have been emerged to obtain the proper operation from wind turbines. However, there are some features needed to be improved to have the best energy conversion system. 
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\nThis thesis is focusing on following areas which are challenges for wind turbine operators encounter: 
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\n1. Improving Total Harmonic Distortion (THD) by designing an advanced control strategy. 
\n2. Inter-turn fault detection at early stage. 
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\nIn the first section of this thesis, a Sliding Mode Control (SMC) based scheme is proposed for a variable speed, direct-driven Wind Turbine Conversion System (WTCS) equipped with Permanent Magnet Synchronous Generator (PMSG) connected to the grid. In this work, diode rectifier, boost converter, Neutral Point Clamped (NPC) inverter and L filter are used as the interface between the wind turbine and grid. This topology has abundant features such as simplicity for low and medium power wind turbine applications. It is also less costly than back-to-back two-level converters in medium power applications. SMC approach demonstrates great performance in complicated nonlinear systems control such as WTCS. The proposed control strategy modifies Reaching Law (RL) of sliding mode technique to reduce chattering issue and to improve THD property compared to conventional reaching law SMC. The effectiveness of the proposed control strategy is explored by simulation study on a 4 KW wind turbine, and then verified by experimental tests for a 2 KW set-up. 
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\nSecond section of this thesis proposes a model-based Fault Detection and Localization (FDL) strategy of a surface-mounted PMSG wind turbine. One of the prevalent faults in wind turbines is Inter-turn Short Circuit (ISC) fault in the generator of WTCS. To elaborate the fault and observe the consequences, a 120 KW wind turbine equipped with PMSG is being modeled while injecting the fault during normal and steady state operation. Geometric Approach (GeA) offers plentiful features for FDL in nonlinear system control applications. It can operate as a built-in function of the WTCS control system in which ISC fault is being detected and localized when occurred in the winding of the stator of PMSG. The GeA is a model-based technique that works based upon the governing equations of the generator of wind turbine. The effectiveness of the proposed FDL scheme is justified by co-simulation of wind energy conversion system using Maxwell, Simplorer, and Matlab software packages.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0060.001
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.237
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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