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Record W1533424159

Grid integration of DFIG-based offshore wind farms with hybrid HVDC connection

2008· article· en· W1533424159 on OpenAlexaff
Honglin Zhou, Geng Yang, Hua Geng

Bibliographic record

VenueInternational Conference on Electrical Machines and Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAC powerInverterOffshore wind powerEngineeringInduction generatorControl theory (sociology)Grid connectionWind powerStatorGenerator (circuit theory)VoltageGridVoltage sourceCommutationDoubly fed electric machineElectrical engineeringPower (physics)Computer scienceControl (management)Physics
DOInot available

Abstract

fetched live from OpenAlex

This paper proposes a new HVDC (High-Voltage DC) transmission topology, its modeling and control method, used for large doubly-fed induction generator (DFIG)-based offshore wind farms. The sending end is a line commutated converter (LCC) with a STATCOM (Static Compensator) while the receiving end is a current source inverter (CSI) using IGBTs. The STATCOM provides stator voltage support for DFIGs, as well as commutation voltage for the LCC. The LCC regulates the active power produced by DFIG wind farms, and transmits it to the onshore inverter through HVDC link. Working in constant voltage control mode, the inverter then feeds the active power into the main AC grid. Simulations verify that, as a combination of existing LCC-HVDC and VSC (Voltage Source Converter)-HVDC technologies, the proposed system not only has the black start capability, possesses fast active power dynamics, but also can provide independent reactive support to the grid.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.026
GPT teacher head0.244
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueInternational Conference on Electrical Machines and SystemsSame topicHVDC Systems and Fault ProtectionFrench-language works237,207