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Record W2139272707 · doi:10.1109/apec.1998.654015

A fast algorithm for voltage unbalance compensation and regulation in faulted distribution systems

2002· article· en· W2139272707 on OpenAlex
Kamal Al Haddad, G. Joós

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsConcordia University
Fundersnot available
KeywordsCompensation (psychology)VoltageVoltage regulationVoltage compensationControl theory (sociology)Voltage optimisationVoltage regulatorEngineeringVoltage sagPower (physics)Computer sciencePower qualityElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

Among the factors affecting power quality in distribution systems are occurrence of faults. This paper discusses an approach to ensure a high quality power supply to critical loads under the most common faults, short circuits on adjacent feeders, resulting in temporary partial or total collapse of one or more phases. The approach is based on static series voltage compensators (single phase voltage source inverters), rated at only a fraction of the load. A voltage regulation algorithm is proposed to ensure fast response of the compensator in suppressing voltage sags and swells. It is demonstrated that good voltage regulation is achieved under the more severe faults. Compensation capability and voltage boost requirements are derived. Control and power circuit design procedures are presented. Static and dynamic performance characteristics are demonstrated on a 2 kVA experimental unit.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.253

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 head0.023
GPT teacher head0.223
Teacher spread0.200 · 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

Quick stats

Citations18
Published2002
Admission routes1
Has abstractyes

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