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The Impact of Synchronous Generator on Voltage Sag Mitigation in Power System Network

2021· article· en· W3208990118 on OpenAlexaff
Umme Kulsum Jhuma, Saad Mekhilef, Shameem Ahmad, Jahurul Islam, Jahidur Rahman Jesan, Md.Motasim Billah

Bibliographic record

Venue2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON) · 2021
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsConcordia University
FundersMinistry of Higher Education, Malaysia
KeywordsVoltage sagGenerator (circuit theory)Fault (geology)MATLABComputer sciencePermanent magnet synchronous generatorVoltageBusbarElectric power systemPower (physics)AC powerReliability engineeringPower qualityElectronic engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Power quality (PQ) has become a major concern in recent years. In order to maintain the proper PQ, it is important to detect the PQ problems through fault analysis and investigate for an adequate way to overcome the problems. Sag, which is a sudden decrease in voltage level, is the most common one in PQ problems almost covering 56% of the entire PQ problems. Therefore, mitigation of voltage sag has drawn much attention. This paper represents the effectiveness of synchronous generator in investigation of Voltage Sag Mitigation in Distribution Network. The selected system for this work is the IEEE 14 bus network. The simulation was carried out using MATLAB software. Two possible scenarios, when sag occurrence and the generator connection bus are same and when sag happens near one bus and the synchronous generator is connected to another bus are taken into consideration for simulation analysis.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.731

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 science0.0010.000
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 head0.020
GPT teacher head0.276
Teacher spread0.256 · 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 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

Citations5
Published2021
Admission routes1
Has abstractyes

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