MétaCan
Menu
Back to cohort
Record W4400411401 · doi:10.1109/tste.2024.3424405

Fault Current Limiting and Grid Code Compliance for Grid-Forming Inverters—Part I: Problem Statement

2024· article· en· W4400411401 on OpenAlex
Ali Azizi, Ali Hooshyar

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

VenueIEEE Transactions on Sustainable Energy · 2024
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrid codeGridLimitingStatement (logic)Computer scienceCompliance (psychology)Code (set theory)Current (fluid)Electrical engineeringReliability engineeringFault (geology)EngineeringSet (abstract data type)AC powerVoltageProgramming languageMechanical engineeringMathematicsGeology

Abstract

fetched live from OpenAlex

Grid-forming (GFM) inverters are controlled to directly regulate the voltage. A major challenge stemming from this control model is that sustaining the voltage during faults would require high currents—beyond the levels that an inverter can withstand. Various fault current limiting (FCL) methods have been developed in recent years for GFM inverter-based resources (IBRs). The theoretical analysis supported by detailed simulation studies in Part I of this paper investigates whether existing FCL methods for GFM inverters can be deemed feasible solutions for future IBR-centric power grids. The challenges revealed for the first time in this paper are multifaceted and depend on the type of the FCL method. The focus is not only on a GFM inverter's internal operation, but also on its impact on the grid and the practical requirements for grid integration of an IBR considering most recent grid codes. Part II of this paper will address these challenges.

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: Methods · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.975

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 head0.026
GPT teacher head0.261
Teacher spread0.236 · 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