Assessing the Technological and Financial Feasibility of PV-Wind Hybrid Systems for EV Charging Stations on Indonesian Toll Roads
Bibliographic record
Abstract
This research evaluates the planning and development of a hybrid renewable energy system that combines photovoltaic (PV) panels and wind turbines for electric vehicle (EV) charging stations along the Cipali, Semarang-Solo, and Surabaya-Mojokerto highways.As energy demands rise and sustainability becomes increasingly recognized, incorporating renewable energy sources is vital for diminishing reliance on fossil fuels.By employing HOMER Pro software, the study analyzes this hybrid approach's operational performance and economic practicality, emphasizing key metrics such as Internal Rate of Return (IRR), Return on Investment (ROI), and Payback Period.The findings reveal that the PV-Wind hybrid system reduces energy expenses and improves the efficiency and sustainability of EV charging infrastructure.Notably, the Surabaya -Mojokerto site displays the most favorable outcomes, featuring an IRR surpassing 25% and the shortest payback period of four years.These results underscore the critical role of effective management, strategic planning, and sustainable development of renewable energy systems to bolster environmentally conscious transportation infrastructure in Indonesia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".