MétaCan
Menu
Back to cohort
Record W2546550191 · doi:10.1109/cogen.2016.7728945

Real time simulation of a microgrid with multiple distributed energy resources

2016· article· en· W2546550191 on OpenAlexaff
Onyinyechi Nzimako, Athula Rajapakse

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of ManitobaRTDS Technologies (Canada)
Fundersnot available
KeywordsMicrogridReal Time Digital SimulatorPhotovoltaic systemDistributed generationDiesel generatorTransient (computer programming)Computer scienceWind powerHardware-in-the-loop simulationTurbineRelayGridVoltagePower (physics)Control engineeringAutomotive engineeringRenewable energyEngineeringElectric power systemElectrical engineeringSimulationDiesel fuel

Abstract

fetched live from OpenAlex

In this research, a real-time simulation model of a medium voltage (MV) microgrid with distributed energy resources (DERs) was developed using the RTDS™ real-time digital simulator. The DERs in this microgrid include a diesel generator, a photovoltaic (PV) system, and a doubly-fed induction generator (DFIG) wind turbine system. The average-value models for the PV and DFIG power electronic interfaces were developed to reduce the hardware requirements on the RTDS. The steady state and transient response of the microgrid when in the grid-connected and islanded modes of operation was shown to give satisfactory performance. The microgrid was interfaced to a protection relay to demonstrate hardware in the loop simulations. This simulation model will be used in future research on developing microgrid protection solutions.

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)0.001
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.002
GPT teacher head0.156
Teacher spread0.154 · 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

Citations33
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicMicrogrid Control and OptimizationFrench-language works237,207