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Modeling and Simulation of a Reduced-Order Single-Phase PQ Inverter Using the Dynamic Phasor Method

2021· article· en· W3212549470 on OpenAlexaff
Udoka C. Nwaneto, Andrew M. Knight

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInverterPhasorMicrogridControl theory (sociology)Computer scienceAC powerPower (physics)Electronic engineeringElectric power systemEngineeringControl (management)Physics

Abstract

fetched live from OpenAlex

The accurate study of an inverter-based energy source is usually performed with the detailed inverter model. However, to perform system-level studies in microgrids, the time to simulate the system increases exponentially as more de-tailed inverter models are added. This paper presents a computationally efficient model of a single-phase PQ inverter based on the dynamic phasor (DP) method. By using the PQ theory and establishing a relationship between the direct-quadrature axis components of the synchronous reference frame and the DP real and imaginary components, independent control of the active and reactive power is realized. The fidelity of the DP-based single-phase PQ inverter model is verified by validating it against a detailed single-phase PQ inverter model implemented in Simulink/Simscape (SS). Simulation results reveal that the DP model can predict transients accurately, using a step size 125 times larger than the detailed SS model’s step size. The proposed DP-based PQ inverter model is suitable for fast-paced system-level studies of a multiple inverter based single-phase microgrid.

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 score0.708
Threshold uncertainty score0.240

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 head0.023
GPT teacher head0.293
Teacher spread0.270 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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