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Record W2296461461

Small Signal Modeling of Resonant Controlled VSC Systems

2010· dissertation· en· W2296461461 on OpenAlexfundno aff
Stephen Podrucky

Bibliographic record

VenueTSpace · 2010
Typedissertation
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsSIGNAL (programming language)AcousticsComputer sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

A major issue with respect to VSC based systems is the propagation of harmonics to DC side loads due to AC voltage source unbalance. Standard dq-frame control techniques currently utilized offer little mitigation of these unwanted harmonics. Recently, resonant controllers have emerged as an alternative to dq-frame controllers for regulation of grid connected converters for distributed resources. Although these control systems behave somewhat similar to dq-frame controllers under balanced operating conditions, their behaviour under unbalanced operation is superior. Currently, there are no linearized state space models of resonant controlled VSC systems.\nThis work will develop a linearized small signal state space model of a VSC system, where resonant current controllers are used for regulation of the grid currents. It will also investigate the stability of resonant controlled VSC based systems using eigenvalue analysis for HVDC applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.259
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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

Citations1
Published2010
Admission routes1
Has abstractyes

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