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Record W2786456277 · doi:10.1109/tii.2018.2799594

Time-Delay Analysis of Wide-Area Voltage Control Considering Smart Grid Contingences in a Real-Time Environment

2018· article· en· W2786456277 on OpenAlexaff
S. M. Muyeen, Ahmed Al‐Durra, Innocent Kamwa, Mohammad A. S. Masoum, Syed Islam

Bibliographic record

VenueIEEE Transactions on Industrial Informatics · 2018
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsTestbedReal Time Digital SimulatorSmart gridPhasorGridController (irrigation)Computer scienceElectric power systemPhasor measurement unitTransmission (telecommunications)Real-time computingEmbedded systemEngineeringPower (physics)Electrical engineeringTelecommunicationsComputer network

Abstract

fetched live from OpenAlex

This paper addresses the time-delay effects of the wide-area monitoring and control systems (WAMCS) in smart power grids which may critically impact system stability. The main purpose is to conduct a detailed delay analysis of the WAMCS in case of grid contingences. This analysis is performed via an advanced WAMCS testbed where a flexible ac transmission system (FACTS) device is utilized and controlled via a wide-area controller (WAC). Phasor measurements units (PMUs) are adopted to collect the real-time measurements for the WAC. The testbed results from an interface of four main segments known as the WAC; the actual FACTS device, the local area controller, and the power grid system along with the PMUs are simulated via a real-time digital simulator. To mimic the real case scenario, both hardware-in-the-loop and software-in-the-loop schemes are adopted in the experimental testbed, considering time-delay effects. The results obtained clarify the effect of delay in WAMCS in case of smart grid contingences.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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

Citations68
Published2018
Admission routes1
Has abstractyes

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