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Record W4406443952 · doi:10.23960/jitet.v13i1.5959

ANALISIS ENERGI LISTRIK PLTS ON-GRID DENGAN BOOST CONVERTER DAN INVERTER BERBASIS MATLAB/SIMULINK

2025· article· id· W4406443952 on OpenAlexaboutno aff
Eva Magdalena Silalahi

Bibliographic record

VenueJurnal Informatika dan Teknik Elektro Terapan · 2025
Typearticle
Languageid
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMATLABInverterElectrical engineeringComputer scienceGridEngineeringOperating systemVoltageMathematics

Abstract

fetched live from OpenAlex

Penelitian ini membahas analisis energi listrik pada pemodelan & simulasi MATLAB/Simulink pada PLTS on-grid menggunakan boost converter dan inverter untuk mensuplai beban listrik rumah tangga 220V satu fasa AC, berlokasi di Samarinda, Kalimantan Timur. Pemodelan & simulasi berdasarkan konfigurasi PLTS on-grid dengan boost converter dan inverter sesuai kebutuhan daya beban listrik rumah satu fasa. PLTS didesain memiliki jam operasional total 288,597653 Ah dan memerlukan arus 65,59 A. Panel surya yang digunakan, Canadian Solar Modul CS60-300P, dengan 5 modul seri, 8 modul paralel, total 40 modul. Total daya listrik beban harian 4.718,49 W, dan total konsumsi energi listrik harian 46,397 kWh. Hasil simulasi, pada sisi keluaran panel PV, diperoleh Vrms 119,7 V, Irms 109.6 A, daya aktif 4.944 W. Pada sisi keluaran inverter, diperoleh Vrms 128,9 V, Irms 37,61 A, daya aktif 315,1 W, daya reaktif 873,6 VAR, pf = 0,3445, f = 49,99 Hz. Pada sisi keluaran beban grid, diperoleh Vrms 220,0 V, Irms 37,6 A, daya aktif 4.555 W, daya reaktif 4.388 VAR, pf = 0,7201 dan f = 50 Hz. Juga diperoleh, rugi-rugi daya 389 W, dan η = 92,13%.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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