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A Modified PUTT Scheme for Transmission Lines Connecting DFIG-Based Wind Farm

2021· article· en· W4205411452 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

Venue2021 IEEE Power & Energy Society General Meeting (PESGM) · 2021
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCrowbarRelayInduction generatorWind powerElectric power transmissionTransmission (telecommunications)Fault (geology)Control theory (sociology)Doubly fed electric machineGridTurbineComputer scienceEngineeringElectrical engineeringPower (physics)AC powerVoltageMathematicsPhysics

Abstract

fetched live from OpenAlex

With the large integration of wind turbine generators (WTGs) in the power grid, the protection of the transmission lines connecting to the WTGs has become a great concern. Doubly fed induction generators (DFIGs) are among the most widely installed WTGs, but the frequency deviation of the fault current measured at the wind farm side relays due to the short circuit behavior of DFIGs with the activation of the crowbar circuit has resulted in the failure of distance relays used for protection of transmission lines connecting DFIGs. This paper proposes a modified permissive underreaching transfer trip (PUTT) scheme that provides fast and reliable protection for the transmission lines connecting DFIG-based wind farms. By adding the frequency tracking elements to the conventional PUTT scheme, the modified scheme correctly blocks the maloperation of the distance elements during external faults, enables the trip of the relay during internal faults, and significantly improves the security of the relay at the wind farm side.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.594
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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