Modeling, Optimization, and Techno-Economic Assessment of a Hybrid System Composed of Photovoltaic-Wind-Fuel Cell and Battery Bank
Bibliographic record
Abstract
Decentralized electricity production from renewable energy sources offers greater security of supply to consumers while respecting the environment.However, the random nature of these sources requires us to establish rules for the sizing and use of these systems in order to make the best use of them.Hybrid renewable energy sources can effectively meet the electric energy needs of the University of Skikda's various structures.This study examines the financial viability of a hybrid renewable-based system that is off the grid and proposed to supply several campuses of the University of Skikda in Algeria with the electricity they need.In order to achieve this, HOMER software is used to optimize and simulate the system under consideration.The results obtained recommend using a system made up of a wind turbine, solar panels, a battery bank, and a fuel cell that can produce electricity at a levelized cost of 0.193 €/kWh.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".