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Record W1616543435 · doi:10.1109/pesgm.2015.7286302

Grid-interactive inverter modeling for power system studies

2015· article· en· W1616543435 on OpenAlexaff
Nayeem Ninad, Dave Turcotte, Tarek H. M. EL-Fouly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsInverterToolboxPhotovoltaic systemComputer scienceMaximum power point trackingGrid-tie inverterRenewable energyGridWind powerPower (physics)Electric power systemSystems engineeringControl engineeringReliability engineeringEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents an overview of the minimal complexity level requirement for modeling generic grid-interactive inverter to conduct power flow, protection, stability and power quality studies. For each functional, control or protection block of the inverter system, it describes the appropriate level of complexity needed to perform each of the power system studies. This work serves as a foundation for the development of an inverter modeling toolbox to facilitate power system studies in renewable energy projects. It intends to address the need of utilities to have access to adequate inverter models to perform accurate integration impact studies of photovoltaic or inverter-based wind projects.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.243

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 head0.039
GPT teacher head0.250
Teacher spread0.211 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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