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Record W2116388938 · doi:10.1109/tpwrd.2010.2042825

Unbalanced Model and Power-Flow Analysis of Microgrids and Active Distribution Systems

2010· article· en· W2116388938 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

VenueIEEE Transactions on Power Delivery · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrogridEngineeringAC powerPower-flow studyThree-phaseSymmetrical componentsPower (physics)Electronic engineeringElectric power systemGenerator (circuit theory)Power flowGridDistributed generationControl theory (sociology)Flow (mathematics)Component (thermodynamics)Frame (networking)VoltageComputer scienceElectrical engineeringRenewable energyMathematicsTransformerTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a three-phase power-flow algorithm, in the sequence-component frame, for the microgrid (μgrid) and active distribution system (ADS) applications. The developed algorithm accommodates single-phase laterals, unbalanced loads and lines, and three/four-wire distribution lines. This paper also presents steady-state sequence-component frame models of distributed energy resource (DER) units for the developed power-flow approach under balanced/unbalanced conditions. The DER models represent the synchronous-generator based and the electronically-coupled DER units. Both constant power (PQ) and regulated-voltage (PV) modes of operation of DER units are considered. The application of the developed power-flow method for two study systems is presented. The study results are validated based on comparison with the detailed solution of the system differential equations in time domain, using the PSCAD/EMTDC software tool.

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 score0.496
Threshold uncertainty score0.616

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 head0.003
GPT teacher head0.175
Teacher spread0.172 · 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