MétaCan
Menu
Back to cohort

A Robust Controller Design for Mitigating Control Loop Interactions in Multi-VSC Systems Built by Multiple Vendors

2022· article· en· W4312833805 on OpenAlexafffund
Fatemeh Ahmadloo, Sahar Pirooz Azad

Bibliographic record

Venue2022 IEEE Power & Energy Society General Meeting (PESGM) · 2022
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvertersController (irrigation)Control theory (sociology)Voltage sourceComputer scienceMATLABControl engineeringControl systemStability (learning theory)Control (management)VoltageEngineering

Abstract

fetched live from OpenAlex

Control loop interactions among voltage-sourced converters (VSCs) sharing the same alternating current (AC) system and the disruptive impacts of these interactions on the stability of multi-VSC systems have been widely studied in the literature. This paper proposes a controller design method for mitigating the negative impact of these interactions on the stability of multi-VSC systems. The proposed controller design approach incorporates the external interactions as uncertainties into the system model and obtains the outer controllers of individual converters using <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H_{\infty}$</tex> controller synthesis. The controllers are designed based on the model of individual VSCs rather than the exact model of the interconnected multi-VSC system, and thus they require only the exact model of individual VSCs and a reduced-order model of coupling dynamics. This modeling requirement ensures design confidentiality in multi-VSC systems built with multiple manufacturers due to the individual design of converter controllers, which does not require the exact model of adjacent converters. The performance of the proposed robust controller is evaluated using time-domain simulations and eigenvalue analysis in MATLAB/SIMULINK.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.254
Teacher spread0.210 · 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.

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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venue2022 IEEE Power &amp; Energy Society General Meeting (PESGM)Same topicHVDC Systems and Fault ProtectionFrench-language works237,207