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A General Operation Model for the Smart Office Testbed Under Consideration of Microgrid Concept

2025· article· en· W4411603182 on OpenAlexaff
Youthanalack Vilaisarn, Aming Phanmixay, Chedtana Chanthasy, Phetphaithoun Bounyavong, Chansamone Liemkeo, Sisavath Khotpanya, Valasy Chounramany, Vorachack Kongphet, J. Cros, Nozomi Takeuchi

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTestbedMicrogridComputer scienceOperations researchComputer securityEngineeringComputer networkArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Abstract An accurate mathematical operation model is the key enabling solution for microgrid operation planning. Nonetheless, the existing models fall short of validating the solutions using only simulation software, which does not reflect a practical condition well. Due to the lack of a practical testbed and benchmark, the solution obtained by the existing models might need to be better validated. Addressing this gap, this work proposed the mathematical model representing the microgrid operation while validated with an implemented testbed smart office at the Faculty of Engineering, NUOL. First, the general operation model is formulated to capture the operation philosophy of the smart office. Subsequently, the proposed model is modified and incorporates the well-known Energy Management System concept with techno-economics under consideration. Finally, the proposed models are implemented and solved in a MATLAB environment while the effectiveness of the models is validated using the extracted practical data from the testbed system.

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)0.000
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 score0.390
Threshold uncertainty score0.284

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 studies0.0000.001
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 head0.009
GPT teacher head0.192
Teacher spread0.182 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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