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Record W2528463412 · doi:10.1109/sege.2016.7589515

Power sharing control and wind power curtailing for offshore multi-terminal VSC-HVDC transmission

2016· article· en· W2528463412 on OpenAlexaff
Mohamed Abdelwahed, Hatem F. Sindi, Ehab F. El‐Saadany

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Waterloo
FundersKing Abdulaziz University
KeywordsOffshore wind powerWind powerVoltage droopHigh-voltage direct currentRenewable energyPower controlEngineeringElectric power systemAC powerPower (physics)ConvertersElectrical engineeringVoltage sourceComputer scienceAutomotive engineeringVoltageDirect current

Abstract

fetched live from OpenAlex

Worldwide, many countries spend billions of dollars on the development of renewable energy sources, especially wind generation, to counter the effects of global warming and in response to other environmental concerns. Given the increasing number of remotely located large power offshore wind farms, power sharing control and voltage regulation are significant challenges in the development of large multi-terminal voltage source converter high-voltage direct current (MT VSC-HVDC) transmission grids. Additionally, a wind-power curtailment algorithm is needed in cases of high windpower generation during low power demand from onshore AC networks. This work presents a power sharing control and wind power curtailment algorithm. This algorithm is based on selecting the optimal droop parameters of the power receiving converters and the reference power output for the offshore wind farms to share the offshore wind energy to the MT HVDC network among different AC grids based on desired shares. These desired power shares are defined to fulfill the active power requirements of the connected systems to achieve their objectives.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.420

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes1
Has abstractyes

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