Modeling of an advanced renewable energy system coupled with hydrogen production and liquefaction for sustainable communities
Bibliographic record
Abstract
The primary objective of this study is to develop a sustainable and efficient renewable energy-based multigeneration system that is specifically designed to meet diverse energy demands, such as heat, cooling, electricity and hydrogen. The system comprises several subsystems: a digester for biomass processing, a solar energy collection system, a thermal energy storage system, a multistage Brayton cycle, a steam Rankine cycle with reheat, a double-effect absorption system, a sonic hydrogen production unit, and a multistage hydrogen liquefaction system. The methodology involves conducting energy and exergy analyses, economic evaluation, and environmental impact assessment to determine the system's performance and viability. The energy efficiency results show that the Brayton cycle, steam Rankine cycle and liquefaction system have efficiencies of 30.92 %, 30.18 %, and 64.53 %, respectively. The exergy efficiencies for these subsystems are 50.10 %, 67.21 %, and 11.29 %, respectively. The double-effect absorption system exhibits energetic and exergetic coefficients of performance of 1.68 and 0.64, respectively. The overall energy and exergy efficiencies of the system are 36.41 % and 55.74 %, respectively. The economic analysis indicates a significant revenue potential, with the project reaching its break-even point in 2031 and achieving a net present value of $6.60 million. The results of an environmental impact assessment study highlight a reduction in CO 2 emissions compared to conventional systems, emphasizing the system's contribution to sustainable energy solutions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".