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Record W4249633129 · doi:10.32920/ryerson.14645781

Current source converters for megawatt wind energy conversion systems

2021· preprint· en· W4249633129 on OpenAlexaff
Jingya Dai

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWind powerSpace vector modulationElectronic engineeringPulse-width modulationConvertersComputer scienceController (irrigation)Current sourceEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

The rapid growth of wind energy market has propelled the research and development of high-power wind turbines in the megawatt range. At this power level, current source converter (CSC) topologies possess favorable features such as simple structure, grid friendly waveforms, controllable power factor, and reliable grid short-circuit protection. This dissertation proposes the use of current source converters for permanent magnet synchronous generator based megawatt wind energy conversion systems (WECS). Related research in terms of converter topology, modulation scheme, control strategy and grid integration are carried out to adapt the proposed configuration for megawatt wind applications. Various current source converter topologies are compared for wind applications. Detailed feasibility study and performance evaluation are conducted based on theoretical analysis and simulation results. Among all, the back-to-back pulse-width modulated (PWM) current source converter is identified as the most promising converter configuration for megawatt WECS due to its high performance, control flexibility and compliance with grid connection codes. A novel multi-sampling space vector modulation (MS-SVM) scheme with superior harmonic performance and controllability is proposed to operate the PWM CSC. The device switching frequency under MS-SVM is investigated and methods to eliminate additional switching are presented. The proposed scheme is compared with the conventional modulation schemes. It is demonstrated that the MS-SVM scheme provides superior performance at low switching frequency. It not only offers high control flexibility but also substantially reduces the low-order harmonics existing in the conventional schemes. System modeling and controller design for the current source converter based WECS are then presented. Dynamic, steady-state and small-signal models are developed for analysis and controller design. An optimum de-link current control scheme is developed to achieve the best dynamic performance and maximize the system overall efficiency. Control strategies such as decoupled active and reactive power control and power feed-forward control are also proposed to further improve the system dynamic performance. Grid integration issues, especially the low-voltage ride-through capability of the current source converter based WECS, are addressed. Challenges for the grid-connected current source converter are identified based on grid code requirements. A unified de-link current control scheme is proposed to assist the system to ride through grid low-voltage faults while maintaining the control capability of active and reactive power during and after the fault. The unified de-link controller can be well embedded in the system control structure. Smooth transitions between normal and fault operations are achieved. Simulation and experimental verifications for various objectives are provided throughout the dissertation. The results validate the proposed solutions for the main challenges of using current source converter in a megawatt WECS.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.221
Teacher spread0.201 · 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; a candidate call from one teacher head, not a consensus.

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

Citations11
Published2021
Admission routes1
Has abstractyes

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