Sustainable Hybrid Solar-Biogas Systems for Electric Vehicle Charging in Tropical Regions: A Techno-Economic Assessment
Bibliographic record
Abstract
This study aims to evaluate the technical and economic performance of the hybrid solar panel and biogas power generation system to support the operation of the electric vehicle charging station in Malang City.The system is designed in two network scenarios, namely grid and off-grid, and analyzed using PVsyst software and HOMER Pro.The simulation results show that the off-grid configuration produces 1,054,693 kWh/year of energy, while the on-grid scenario achieves 985,216 kWh/year.The Performance Ratio value of the photovoltaic system is 0.83, reflecting relatively high reliability in humid tropical climate conditions.Economically, the off-grid system has a Levelized Cost of Energy (LCOE) of IDR 1,825.07/kWhwith a payback period of 4.13 years, while the on-grid scenario shows an LCOE of IDR 3,610.73/kWhwith a payback period of 2.64 years.This study shows that integrating hybrid systems is feasible as a clean and efficient energy solution to support the electric vehicle ecosystem, especially in urban areas with high renewable energy potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".