Technical and economic assessments of a novel multigeneration system based on desalination and liquid air energy storage
Bibliographic record
Abstract
The practical pioneering methodologies can be employed to improve the efficiency of energy systems. To attain the desired objectives in exergy and economic studies, original configurations alongside practical methodologies are sought after. In this research, an advanced multigeneration system involving liquid air energy storage and desalination system is designed. The system has the potential to generate a wide range of products to increase the preferences of the system both technically and economically. The system produces sodium hypochlorite, cooling, electricity, heating, hydrogen, and potable water. The results from the conducted research revealed that the system can generate 5901 kW electricity power while the round-trip efficiencies from energetic and exergetic prospects are 65.8 % and 59.6 %, respectively. The total EDR from the system is approximately 16 MW. The noteworthy outcomes from economic assessments revealed that the payback periods of the system with and without renewable energy-powered systems are 2.7 and 2.9 years, respectively. Combining chemical and thermomechanical energy storage systems with process facilities provides a cutting-edge subject matter. The integrated energy storage system with the desalination unit indicates that over the peak-shaving periods, auxiliary products can be produced while renewable energy systems charge the energy storage system.
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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 | 0.001 | 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) | 0.003 | 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".