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A Comparative Study on Control Loop Interactions in VSC-HVDC Systems

2020· article· en· W3114567909 on OpenAlexaff
Fatemeh Ahmadloo, Sahar Pirooz Azad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsControl theory (sociology)Phase-locked loopLoop (graph theory)VoltageConvertersVoltage sourceMaximum power transfer theoremTransfer functionControl systemComputer scienceAC powerBlock diagramPower (physics)EngineeringElectronic engineeringPhysicsMathematicsControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

Voltage source converters (VSCs) embedded in high voltage direct current (HVDC) systems include multiple interconnected control loops and a phase-locked loop (PLL), which interact with each other. These loops control a combination of the DC voltage, active power, reactive power and AC voltage of the converter. This paper investigates the interaction between the various control loops in a VSC-based HVDC system. The main focus of this paper is to identify the particular combination of direct (d)-axis and quadrature (q)-axis control loops, which results in the most significant interaction of the loops. At first, a comprehensive block diagram which includes all the possible combination of various control loops is presented. Then, the infinity norm of the system transfer functions from the input of one loop to the output of the other loop is used to quantity the loops' interaction level. Furthermore, the impact of adjacent AC system strength on the loop interactions is studied. Simulation results using Matlab/Simulink demonstrate that the closed-loop combination of the AC voltage and the DC voltage controllers results in the highest interaction level among the various control loop combinations.

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: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.457

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 head0.051
GPT teacher head0.294
Teacher spread0.244 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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