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Record W1765904459 · doi:10.1109/pesc.1999.789039

Control algorithms for series static voltage regulators in faulted distribution systems

2003· article· en· W1765904459 on OpenAlexaff
Kamal Al Haddad, G. Joós, S. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsConcordia University
Fundersnot available
KeywordsHarmonicsUninterruptible power supplyControl theory (sociology)VoltageCompensation (psychology)Fault (geology)Voltage regulationEngineeringElectric power systemPower (physics)Power controlComputer scienceControl engineeringControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

Power quality and availability are becoming important issues for critical and sensitive loads. This paper presents a viable alternative to the use of uninterruptible power supplies solutions for three-phase load voltage support. This support is provided by a series compensator structure with a rating equal to a fraction of the load. The paper discusses control issues and proposes a control algorithm that results in a fast dynamic response and is insensitive to the type of fault and to disturbances and harmonics present on the power network. The technique is applied to a faulted distribution system to compensate for voltage sags. The steady state compensation capability of the scheme is derived. The dynamic performance is analyzed and verified through experimental tests on a 2 kVA prototype power conditioner. Practical issues, such as power and control circuit design and converter ratings are considered.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.240
Teacher spread0.221 · 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

Citations28
Published2003
Admission routes1
Has abstractyes

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