MétaCan
Menu
Back to cohort
Record W4317438378 · doi:10.1063/5.0112695

Optimization of a reliable grid-connected PV-based power plant

2023· article· en· W4317438378 on OpenAlexaff
Muhammad Mahbubur Rashid, Mohammad Yeakub Ali, Muhammad Hasibul Hasan, Nur Syamimi Mokthar

Bibliographic record

VenueAIP conference proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIconSearch engine optimizationDownloadCitationComputer scienceInformation retrievalGridWorld Wide WebOnline searchSearch engineGeography

Abstract

fetched live from OpenAlex

PV system can be considered as promising technologies in generating electrical energy. In order to meet the high demand of electric consumption much research on PV system have been done. This project focuses on maximizing the output energy from PV panel and maintain the amount of energy that has converted by a PV panel. Maximum power point tracking (MPPT) has been used in this project in optimizing the PV system. One of the methods of the MPPT technique which is Perturb and Observe (P&O) algorithm, easy to implement and has efficient performance in solving the optimization problem. The performance of P&O algorithm has been analysed through the simulation in MATLAB and experimental result.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.191
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

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicMicrogrid Control and OptimizationFrench-language works237,207