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Record W2905551267 · doi:10.1109/ecce.2018.8557761

Implementation and CHIL Testing of a Microgrid Control System

2018· article· en· W2905551267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsOpal-Rt Technologies (Canada)McGill University
Fundersnot available
KeywordsMicrogridComputer scienceControl (management)Control systemEngineeringElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

With the growing deployment of microgrids, it is urgent to standardize microgrid control system and the test procedure. In this paper, implementation and testing of a microgrid control system with transition and dispatch function is presented. To alleviate power fluctuations due to renewable energy and control the power at point of interconnection (POI) to zero for planned islanding, tie-line flow control is adopted in grid-connected mode. Voltage-frequency control applied to energy storage system can achieve stable frequency and active re-synchronization in islanded mode. State-of-Charge and power-limiting based dispatch rules are employed in both grid-connected and islanded mode to maintain power balance while reducing fuel consumption. Power balancing upon unplanned islanding is achieved by emergency dispatch. Technique for smooth transition is also adopted to reduce the impact on the breaker at POI and mitigate the disturbance of distributed renewable resources during islanding/reconnection. The control algorithm is implemented with controller hardware-in-the-loop (CHIL) test bench.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.187

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 head0.004
GPT teacher head0.190
Teacher spread0.185 · 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

Quick stats

Citations17
Published2018
Admission routes1
Has abstractyes

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