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Record W4382025599 · doi:10.54463/je.v2i2.51

PERENCANAAN PEMBANGKIT LISTRIK TENAGA SURYA ON-GRID DI ATAP GEDUNG JURUSAN TEKNIK ELEKTRO POLITEKNIK NEGERI AMBON

2023· article· id· W4382025599 on OpenAlexaff
Nabila Istiqamah Latupono, Jacob J. Rikumahu, Lory Marcus Parera

Bibliographic record

VenueJurnal ELKO (Elektrikal dan Komputer) · 2023
Typearticle
Languageid
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsOperating systemElectrical engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Dalam penelitian ini membahas tentang perencanaan PLTS terhubung ke grid untuk melayani suplai daya listrik di Jurusan Teknik Elektro Politeknik Negeri Ambon. Potensi energy surya di Maluku dan Maluku Utara sendiri mencapai 738 gigawatt dan belum dimanfaatkan secara optimal,Selama ini Jurusan Teknik Elektro Politeknik Negeri Ambon mendapatkan suplai daya listrik hanya bersumber dari PLN saja. Sistem pembangkit listrik tenaga surya On-Grid yang dinamis dapat menjaga stabilitas sistem tenaga listrik mengingat lampu pada beberapa ruang kuliah di Jurusan Teknik Elektro sering tiba-tiba redup dan terang kembali hal ini terjadi karena adanya ketidakstabilan tegangan listrik. Masuknya pembangkit listrik tenaga surya ke jaringan listrik utama dapat mengoptimalkan pemanfaatan energi dari sel surya (photovoltaic) untuk menghasilkan energi listrik semaksimal mungkin dan dapat mengurangi kapasitas atau operasi pembangkit konvensional sehingga dapat mengurangi penggunaan bahan bakar. Beban listrik yang tersambung dengan sistem PLTS dan grid menggunakan energi yang sama dengan yang disalurkan oleh PLTS dalam jangka waktu tertentu. Dalam hal ini, grid menjadi penyimpan atau pemberi pinjaman sementara untuk pemenuhan permintaan daya listrik. Sehingga dengan penerapan konsep ini kita hanya mengeluarkan biaya investasi dari sistem PLTS tanpa baterai dan biaya sewa jaringan di sistem PLTS – Grid.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.217
Teacher spread0.206 · 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
Published2023
Admission routes1
Has abstractyes

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