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Validating IEEE 1547 Capabilities of DER Inverter Model Using a Real-Time Simulated Inverter Laboratory Testbed

2022· article· en· W4296443139 on OpenAlex
Nayeem Ninad, Eugene Desjardins-Couture, Estefan Apablaza-Arancibia

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsNatural Resources Canada
FundersResearch and Development
KeywordsTestbedInverterGridComputer scienceRenewable energyDistributed generationReliability engineeringEmbedded systemEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

With higher renewable energy penetration in the electric grid, the need for electromagnetic transient (EMT) models of inverter based resources (IBRs) with grid support functions (GSFs) is inevitable. Validated EMT models of IBRs, especially inverter based distributed energy resources (DERs), will allow system planners, researchers and grid operators to properly understand the impact of these resources. In this regard, a real-time grid code testing architecture, which includes the modeling of a solar inverter with different GSFs, was developed. Then, the PV inverter GSFs were programmed for IEEE 1547 and the GSFs of the overall model were validated using the GSF test procedures from IEEE 1547.1 standard. The results were also compared with an actual commercial PV inverter unit. This real-time grid code testing platform is an important tool to model the GSFs of IBRs/DERs from different jurisdictions. Furthermore, associated test procedures could be refined during development by the working group.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.989

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)0.0010.000

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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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