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Record W4382540342 · doi:10.18280/mmep.100330

Evaluating the Effects of Air Cooling on Photovoltaic Module Performance in Hot Climates: A Comprehensive Numerical and Experimental Investigation

2023· article· en· W4382540342 on OpenAlexvenueno aff
Ahmed J. Hamad, Fawizea M. Hussein, Ali Lateef Tarish

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemEnvironmental scienceEngineering physicsMeteorologyAerospace engineeringArchitectural engineeringComputer scienceEngineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

The performance of solar photovoltaic (PV) modules is significantly impacted by heat accumulation within the module materials, resulting from solar irradiance.This heat accumulation leads to increased module temperatures and decreased output power.Consequently, enhancing the cooling performance of PV modules can improve their output power, electrical efficiency, and extend their operational lifespan.In this study, the influence of air cooling on solar PV module performance under hot climatic conditions was investigated experimentally and numerically for various ambient temperatures (35, 40, 45℃) and irradiance levels (G: 800, 900, 1000 W) at different air flowrates.A numerical investigation was conducted using a turbulent flow simulation model, solved with COMSOL Multiphysics 5.4 software.Results demonstrated a considerable reduction in PV module temperature as the cooling air flowrate increased under diverse testing conditions.Module temperature increments of approximately 1.8% and 4% were observed for G=900 W and 1000 W, respectively, when compared to G=800 W. The output power of PV modules incorporating air cooling exhibited enhancements of roughly 8.2%, 7%, and 5.4% for irradiances of 800, 900, and 1000 W, respectively, compared to those without cooling.Furthermore, the electrical efficiency of PV modules with air cooling improved by approximately 4%, 4.4%, and 5% for irradiances of 800, 900, and 1000 W, respectively, in comparison to those lacking cooling mechanisms.

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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.532

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 head0.043
GPT teacher head0.274
Teacher spread0.230 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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