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Record W3018327636 · doi:10.1109/tpel.2020.2989197

Modular Interline DC Power Flow Controller

2020· article· en· W3018327636 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Alberta
FundersNational Key Research and Development Program of China Stem Cell and Translational ResearchScience and Technology Project of State Grid
KeywordsModular designController (irrigation)Power (physics)Power flowLine (geometry)AC powerPower controlControl theory (sociology)GridComputer scienceTopology (electrical circuits)EngineeringFlow (mathematics)Electronic engineeringControl engineeringElectrical engineeringElectric power systemControl (management)VoltagePhysicsMathematics

Abstract

fetched live from OpenAlex

DC power flow controller (DCPFC) is regarded as an effective technology to improve the active power distribution capability in a complex dc grid. Among different types of DCPFCs, the interline dc power flow controller (IDCPFC) can realize multiline power flow control functions in a complex dc grid. In this article, a modular multiline IDCPFC has been proposed via a transformerless structure. Specifically, the n-line IDCPFC can actively control (n-1)-line power flow based on the theoretical analysis. The proposed technology is analyzed in detail, including topology, operation principle, and control strategy. As a case study, a three-line IDCPFC is implemented in this article. Both simulation and experimental results are obtained to show that the proposed IDCPFC can effectively control multiline power flows under various conditions.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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