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Record W2913412069 · doi:10.5539/jas.v11n3p137

FOTODIM—Software for Sizing of Photovoltaic Systems

2019· article· en· W2913412069 on OpenAlexvenueno aff
Daisy Regina dos Santos, Carlos Eduardo Camargo Nogueira, Félix Augusto Pazuch, Francielle Pareja Schneider, Jair Antônio Cruz Siqueira, Vitor Lisboa Nogueira, Samuel Nelson Melegari de Souza, Vander Fabio Silveira

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSizingPhotovoltaic systemGridNet present valuePayback periodComputer scienceRooftop photovoltaic power stationPhotovoltaicsInternal rate of returnSoftwareReliability engineeringAutomotive engineeringEngineeringElectrical engineeringProduction (economics)MathematicsVoltageOperating system

Abstract

fetched live from OpenAlex

This study addresses the development of a computational tool for the sizing of photovoltaic systems interconnected to the grid (grid-tied) and isolated (off-grid) systems. The calculations for the sizing were obtained from the CRESESB Engineering Manual for Photovoltaic Systems, the GREENPO Photovoltaic Systems Technology, Design and Installation Manual, and the BLUESOL Solar System Introduction Digital Book. With knowledge of the latitude, longitude and altitude data of the site, the tool calculates the angle of the modules for better absorption of the photovoltaic radiation. For systems connected to the grid, it is also necessary to provide information on the consumption of the building to be serviced by the photovoltaic system. For isolated systems, in addition to information on the site, it is necessary to know the demand and consumption of the building. Decision-making criteria are based on economic analysis, according to indexes such as Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback. The screens developed for the sizing tool and examples of sizing of both photovoltaic systems are presented as results, through tables and graphs. The developed software is reliable, and all calculations have theoretical basis.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.015

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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreSoftware

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
Published2019
Admission routes1
Has abstractyes

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