Performance Analysis of Multi-Oriented Residential Rooftop PV System in Indonesia Towards Net Zero Emission by 2060
Bibliographic record
Abstract
Performance of 5 kWp Multi-Oriented Photovoltaic (PV) Power Plant installed in one of the houses in Jakarta, Indonesia has been obtained by evaluating the performance of the rooftop PV Power Plant system.To calculate the impact of the system on Net Zero Emissions (NZE), it is necessary to evaluate the performance to determine the quality of the installed system's performance by calculating the Performance Ratio (PR) and the Capacity Factor (CF).The data needed to calculate PR and CF consist of PV array outputs; irradiation that falls on the surface of the array, ambient temperature and PV module temperature.These data were collected for one year from January to December 2022.From the calculation, the system yields 76.07%PR, 11.13% CF, and CO2 emissions reduction was 3,703.63 kg/year.As a comparison and reference, a PR and CF system calculation is carried out with PVSyst software which simulation results can be used to design a PV Power Plant system with the proper orientation both multi and single oriented for optimal performance.The technical quality of a good PV Power Plant system is needed to support the achievement of Indonesia's target towards NZE in 2060.The results of the study show that compared to the system PR, the performance evaluation of the PV Power Plant system based on CF systems is more appropriate to be used as a benchmark because it is more oriented to the output system which is directly proportional to the reduction of CO2 emissions.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".