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Record W2556836235 · doi:10.1109/iecon.2015.7392932

Stability and accuracy evaluation of a power hardware in the loop (PHIL) interface with a photovoltaic micro-inverter

2015· article· en· W2556836235 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsInterface (matter)Photovoltaic systemSoftwareStability (learning theory)InverterPower (physics)Computer scienceRepresentation (politics)Topology (electrical circuits)Electronic engineeringHardware-in-the-loop simulationGridElectrical engineeringEngineeringEmbedded systemVoltagePhysicsOperating systemMathematics

Abstract

fetched live from OpenAlex

Stability and accuracy of PHIL simulation depends upon the characteristics of the interface between the RTS and the hardware device under test. Even when stable PHIL is achieved, the non-idealities in the PHIL interface introduces inaccuracies in the simulation results. Software models that include representation of the PHIL interface provide a method to evaluate the stability and accuracy of a PHIL interface. In most instances the required parameters and circuit topology of the power devices that are to be tested are unavailable, thus making it difficult to prepare the required software models. This paper will discuss the challenges of evaluating the stability and accuracy of a PHIL simulation with a grid-connected photovoltaic micro-inverter whose parameters and converter topology are unknown.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.267
Teacher spread0.229 · 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

Citations30
Published2015
Admission routes1
Has abstractyes

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