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Record W2620605709 · doi:10.1049/iet-rpg.2016.0459

Active and reactive power control of wind farm for enhancement transient stability of multi‐machine power system using UIPC

2017· article· en· W2620605709 on OpenAlex

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

VenueIET Renewable Power Generation · 2017
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTransient (computer programming)AC powerControl theory (sociology)Wind powerStability (learning theory)Electric power systemPower (physics)Power controlComputer scienceControl (management)EngineeringPhysicsElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This study discusses the connection of wind farms (WFs) to power system through unified inter‐phase power controller (UIPC) for enhanced transient stability of the power system. The power circuit of the UIPC is based on the conventional inter‐phase power controller (IPC), which its phase‐shifting transforms are substituted by two series converters and one shunt converter. During fault condition, the WF connected through UIPC acts as STATCOM with capability of the active and reactive power control at UIPC connecting point. Based on the UIPC model and low‐voltage ride‐through requirements of the new grid codes, a control system for active and reactive powers control is proposed for enhancement transient stability of power system. The proposed approach is validated in a four‐machine two‐area test system. Power systems computer aided design (PSCAD)/EMTDC simulation results demonstrate that the UIPC provides an effective solution for enhancement of transient stability of power system including WFs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.246
Teacher spread0.223 · 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