MétaCan
Menu
Back to cohort
Record W2767548508 · doi:10.1109/ias.2017.8101749

New control approach for high performance of offshore wind farm under DC fault using three-level NPC VSC-HVDC and DC chopper

2017· article· en· W2767548508 on OpenAlexaff
Seghir Benhalima, Ambrish Chandra, Miloud Rezkallah, Shweta Singh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsChopperOffshore wind powerHigh-voltage direct currentEngineeringFault (geology)ConvertersDirect currentVoltage sourceRobustness (evolution)Electric power systemWind powerControl theory (sociology)VoltageElectronic engineeringPower (physics)Computer scienceElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

In this paper new control approach to achieve high performance under DC fault using three-level NPC voltage source converter based high voltage direct current (VSC-HVDC) transmission for offshore wind farm, are proposed. The proposed configuration allows optimal integration of highly distributed large scale offshore wind farm and demonstrates good performance of VSC-HVDC under presence of quickly cleared DC line fault. Furthermore, it is able to maintain stable operation of the existing power converters. The proposed control is based on detection of the positive to ground fault by measuring the level of cable voltage and the derivatives of the DC voltage and current. In addition, the protection control action of DC chopper extinguishes the fault current to restore the power transmission after the fault has been cleared, improving network reliability and power quality. Modeling and simulation tests are provided to validate the robustness of the proposed design, as well as, the developed control approaches.

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 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 score0.492
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.245
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicHVDC Systems and Fault ProtectionFrench-language works237,207