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Record W2764278808 · doi:10.1109/ccta.2017.8062771

Harmonic reduction via optimal power flow and the frequency coupling matrix

2017· article· en· W2764278808 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

Venue2017 IEEE Conference on Control Technology and Applications (CCTA) · 2017
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTotal harmonic distortionHarmonicsHarmonicControl theory (sociology)Harmonic analysisVoltageElectronic engineeringComputer scienceTopology (electrical circuits)EngineeringPhysicsElectrical engineeringAcoustics

Abstract

fetched live from OpenAlex

In this paper we propose a new optimal power flow scheme that takes into account the harmonics generated by power electronics interfaced distributed generation (DG). The objective is to minimize the cost of generation under constraints on the total harmonic distortion (THD) of voltage. The frequency coupling matrix (FCM) is used to model the harmonic current injected by a converter. Network current and voltage are modeled for each harmonic frequency. Constraints limiting the maximum voltage THD are introduced to the three-phase optimal power flow (OPF) problem. We construct a semidefinite relaxation, which can be solved using commercially available software packages. We give numerical results for the harmonic-constrained optimal power flow for two test systems.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.713

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 studies0.0010.001
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 head0.011
GPT teacher head0.249
Teacher spread0.239 · 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