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Record W4225935105 · doi:10.1109/tia.2022.3159495

Development of Interface Model and Design of Compensator to Overcome Delay Response in a PHIL Setup for Evaluating a Grid-Connected Power Electronic DUT

2022· article· en· W4225935105 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2022
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInterface (matter)InverterElectronic engineeringGridTransformerEngineeringControl theory (sociology)Electric power systemResistorFrequency responsePower electronicsControl engineeringComputer sciencePower (physics)Electrical engineeringVoltage

Abstract

fetched live from OpenAlex

The power hardware in the loop (PHIL) is an attractive way of performing various studies for testing a non-linear power electronic converter in laboratory scale and yet get a result that resembles an actual like scenario. This approach, however promising, suffers from various stability problems arising due to the interface between the hardware and software environment required to create a PHIL. This article presents a thorough analysis of the stability problem in PHIL by individually studying the interface device that forms the ideal transformer method (ITM) interface. The model of the ITM interface is developed and verified experimentally using a frequency sweep approach. The developed model can serve as a tool to understand the factors affecting the stability in a PHIL set up. Utilizing the developed model, this article proposes a Smith predictor (SP) compensator that eliminates the effect of delay in the closed loop response of the system. The SP compensator is designed and implemented in a real time digital simulator platform and the performance of the compensator is verified through various experiments. A case study of a compensator employed resistor divider network is presented to validate a stable PHIL, both theoretically and experimentally. Further, the proposed compensator is tested to evaluate a 250 W grid connected photovoltaic inverter in a PHIL.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.624

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 head0.035
GPT teacher head0.297
Teacher spread0.262 · 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