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Record W2002380304 · doi:10.1109/epec.2013.6802959

Modeling solar photovoltaic cell and simulated performance analysis of a 250W PV module

2013· article· en· W2002380304 on OpenAlexaff
Mohammad Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsAlberta EnergyWind Energy Institute of CanadaRoyal Military College of CanadaSaint Mary's University
Fundersnot available
KeywordsDatasheetPhotovoltaic systemMATLABSolar irradianceSolar cellSolar energyIrradianceComputer scienceElectronic engineeringEngineeringElectrical engineeringOpticsMeteorologyPhysics

Abstract

fetched live from OpenAlex

The main purpose of this study is to develop the mathematical model of solar photovoltaic (PV) cell and to simulate its behavior. The study includes the performance analysis of a 250W PV module and its behavior on different temperature conditions, irradiance levels. It also focuses on the effects of varying shunt and series resistances. The model has been developed considering possible environmental effects on solar PV generation. The results of the characteristics curves in this paper are compared to the curves provided by the CS6P-250M PV module datasheet. Using this model it is possible to simulate the behavior of any large scale PV array or solar Photovoltaic Energy Conversion Systems (PVECS). The model was developed by using Matlab®/Simulink” software. This model can be used for further simulation based research and analysis on PVECS.

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)0.000
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations35
Published2013
Admission routes1
Has abstractyes

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