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Record W2391412580

Study of the establishment of DC voltage and start strategy of UPQC

2012· article· en· W2391412580 on OpenAlexaff
Tan Zhi-li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering and Test Systems
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsCapacitorCompensation (psychology)VoltageMATLABSequence (biology)EngineeringPower (physics)Control theory (sociology)Computer scienceElectronic engineeringControl engineeringElectrical engineeringControl (management)Artificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Unified power quality conditioner (UPQC) is a kind of comprehensive power quality compensation equipment with complex circuit and structure. Starting UPQC involves the establishment of the DC side capacitance voltage, logical sequence of series, parallel compensator and load, namely each part of UPQC must have a certain of start time sequence and logic control strategy. This paper discusses three establishing methods of the capacitor voltage on DC side of UPQC, which can be considered as DC power, and analyzes their advantages and disadvantages, too. Then the control logic of UPQC starting, namely the order of power supply, series and parallel compensator, and load, is discussed based on the different capacitor voltage establishment methods. The reason of adopting these switching sequences is analyzed and the detailed start logic diagram is drawn. Finally, different switching sequences are simulated by MATLAB/Simulink. The simulation results show that the proposed strategy is effective. This work is supported by National Natural Science Foundation of China (No. 50807049).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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