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Record W2114641420 · doi:10.5897/jmer.9000017

Enhanced power transfer capability by using SSSC

2011· article· en· W2114641420 on OpenAlexvenueno aff
Akhilesh A. Nimje, Chinmoy Kumar Panigrahi, Ajaya Kumar Mohanty

Bibliographic record

VenueMechanical Engineering Research · 2011
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsAC powerMaximum power transfer theoremTransmission lineControl theory (sociology)Unified power flow controllerElectric power transmissionFlexible AC transmission systemVoltagePower factorStatic VAR compensatorPower flowElectric power systemCompensation (psychology)EngineeringElectronic engineeringComputer sciencePower (physics)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

Static Synchronous Series Compensator (SSSC) is a voltage sourced converter based series FACTS device that provides capacitive or inductive compensation independent of line current. This paper presents the achievement of the required active and reactive power flow into the line for the purpose of compensation as well as validation of enhancement of the power transfer capability of a transmission line when Interline Power Flow Controller acts as standalone as SSSC. The effect of variation of the phase angle of the injected voltage on the power system parameters such as effective sending end voltage, effective transmission angle, active power, reactive power, and overall power factor with and without SSSC have also been incorporated. The numerical results for the test case have been presented to demonstrate the performance and its applicability on a transmission line.   Key words: Coupling transformer, flexible ac transmission (FACTS), interline power flow controller (IPFC), static synchronous series compensator (SSSC), voltage sourced converter (VSC), static compensator (STATCOM).

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.059
GPT teacher head0.285
Teacher spread0.226 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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