PERANCANGAN DAN SIMULASI PLTS ATAP 1 KWP MENGGUNAKAN HELIOSCOPE
Bibliographic record
Abstract
Solar Power Plant (PLTS) as one of the renewable energy sources that is being focused on itsdevelopment. This article discusses the design and simulation of the performance of a 1 kWp rooftopsolar power plant using a Helisocope. The input data required by the Helioscope is PLTS technicalspecifications such as solar panel technology, inverter type, number and type of modules selectedand land area. The location data required by the PLTS system includes the coordinates, the type ofroof of the building, the environment around the PLTS and meteorological data. The 1 kWp PLTS roofsystem designed at the location that the author uses uses 7 pcs Canadian Solar 195 Wp panels, 1pcs 1 kW AEC inverter, installed on the roof of the building facing north, and connected to the PLNnetwork via a net meter. This 1 kWp rooftop PLTS is capable of producing an average daily averageof 5,48 kWh, 41,07 kWh weekly, 164,29 kWh monthly, and annual 1971,5 kWh. Energy productionvaries by an average of 8% per month with the minimum production in January of 135,1 kWh and thehighest in July of 184,5 kWh. The designed 1 kWp PLTS roof produces a performance ratio of 73,6%with the irradiation received in a year reaching 1859,2 kWh/m2. The initial investment required to builda 1 kwp PLTS roof is IDR. 20.000.000.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".