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Record W7035751189

Análise da variação da potência do arranjo fotovoltaico para operação de um inversor projetado

2022· dissertation· en· W7035751189 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Repository of the Federal Technological University of Paraná (RIUT) (Federal University of Technology – Paraná) · 2022
Typedissertation
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemInverterVoltageElectricityElectric energyVoltPower (physics)Maximum power point tracking
DOInot available

Abstract

fetched live from OpenAlex

Through the development of society it can be said that the use of electricity is one of its main needs. With the accelerated growth of technologies and industrialization, electric energy is indispensable, linked to the concept of sustainable development, the search for alternative sources becomes increasing, with this, there was a greater demand for photovoltaic energy. For this study, the influence of the power variation of the input photovoltaic array on the period of operation of a single­phase inverter was analyzed. The data used were obtained using the PVsyst software. The values of temperature and hourly irradiation were found for the day with the highest and lowest irradiation in each month for the city of Medianeira­PR. Next, the temperature and irradiation were used to plot the I­V and P­V graphs per hour of the CS3W­450MS photovoltaic panel from the Canadian Solar company. All data obtained were exported to Excel so that the analysis could be performed. For the considered inverter to work properly, it is necessary that the minimum voltage at the input is 190V and the current is 1A, and for that an arrangement with 5 panels in series was considered. From the graphs, it can be seen that in January (summer) the inverter would work from 6 am to 6 pm. In the month of July (winter) the panel arrangement provides the voltage and/or current needed only from 8 am to 4 pm. For any change in the panel model or change in location, the analyzes must be carried out to verify the times that present the minimum conditions for the operation of the inverter.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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