MétaCan
Menu
Back to cohort
Record W2071780137 · doi:10.1109/tie.2014.2367456

Impact of Communication Delays on Secondary Frequency Control in an Islanded Microgrid

2014· article· en· W2071780137 on OpenAlexafffundabout
Shichao Liu, Xiaoyu Wang, Peter Liu

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrogridRobustness (evolution)Automatic frequency controlControl theory (sociology)Scheduling (production processes)Computer scienceRobust controlControl engineeringController (irrigation)EngineeringControl systemControl (management)Telecommunications

Abstract

fetched live from OpenAlex

Low-bandwidth communication channels are used to support the information exchange between a microgrid centralized controller and local controllers in the secondary frequency control of an islanded microgrid. However, the impact of the inherent time delay in these communication channels on the microgrid performance has not been taken into account when the secondary frequency controller is designed. This paper investigates the effect of the communication delays on the secondary frequency control of an islanded microgrid with multiple distributed generators. A small-signal model-based method is introduced for the microgrid to find delay margins below which the microgrid can remain stable. By performing a series of trial studies, the relationships between secondary frequency control gains and delay margins are obtained. A gain scheduling approach is also proposed to compensate the effect of the communication delay on the secondary frequency control. Results from the Canadian urban distribution system have verified that communication delays can adversely affect the microgrid secondary frequency control, and the proposed gain scheduling approach can improve the robustness of the microgrid secondary frequency controller to communication delays.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.010
GPT teacher head0.226
Teacher spread0.215 · 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

Citations408
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueIEEE Transactions on Industrial ElectronicsSame topicMicrogrid Control and OptimizationFrench-language works237,207