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Record W2037409445 · doi:10.1049/iet-rpg.2013.0416

Optimal sizing approach for islanded microgrids

2014· article· en· W2037409445 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

VenueIET Renewable Power Generation · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsSizingComputer scienceMathematical optimizationReliability engineeringEngineeringMathematicsChemistry

Abstract

fetched live from OpenAlex

This study proposes a single‐objective optimal sizing approach for an islanded microgrid (IMG). The approach determines the optimal component sizes for the IMG, such that the life‐cycle cost is minimised while a low loss of power supply probability (LPSP) is ensured. As wind speed and solar irradiation exhibit both diurnal and seasonal variations, the proposed algorithm takes advantages of the typical meteorological year‐based chronological simulation and enumeration‐based iterative techniques. The mathematical models presented in this study for the IMG components consider the non‐linear characteristics as well as the reactive power. The LPSP is also formulated based on the supply‐demand balances of both real and reactive powers, and an economic evaluation model is presented. The proposed sizing approach identifies the global minimum, and simultaneously provides the optimal component sizes as well as the power management strategies. This study also presents a number of sensitivity analyses as well as comparisons with a commercial software package.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score0.633

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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