A multi-carrier energy system for electricity, desalinated water, and hydrogen production: Conceptual design and techno-economic optimization
Bibliographic record
Abstract
This study investigates the integration of multiple energy carriers within a unified, multi-carrier energy system using an energy cascade approach. The system harnesses geothermal energy to power interconnected subsystems, including an organic Rankine cycle (ORC), liquefied natural gas (LNG), and a solid oxide fuel cell (SOFC) stack. The dual ORC system and LNG stream are directly fed from the geothermal source, while the SOFC stack uses methane produced during LNG regasification. Besides electricity, the system generates hydrogen and desalinated water by incorporating a proton exchange membrane (PEM) electrolyzer and a reverse osmosis (RO) desalination plant. The electricity produced by the upper ORC powers the PEME for hydrogen production, while freshwater production is supported by the combined output from the lower ORC, LNG turbine, and SOFC. A detailed thermo-economic analysis assesses the system's efficiency and economic feasibility. Optimization efforts focus on three areas: electrical efficiency, hydrogen, and freshwater production, using artificial neural networks (ANN) and genetic algorithms (GA). The optimization results reveal that Ammonia-propylene excels in electrical efficiency, R1234ze(Z)-ethane in net power output, R1233zd(E)-propylene in cost-effectiveness, R1234ze(Z)-ethane in hydrogen production, and Ammonia-ethane in water production. The study offers valuable insights into enhancing the efficiency, cost-effectiveness, and sustainability of integrated energy systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".