A synchronized multi-staged thermal energy storage system for sustainable hydroponic greenhouses
Bibliographic record
Abstract
This study develops and evaluates an innovative integrated solar-powered system which is integrated with a novel three-level synchronized latent heat storage system to provide a sustainable and continuous supply of electricity, freshwater, and heat for greenhouse applications, particularly focusing on arid regions like Doha, Qatar. This latent heat storage system offers better management and lower exergy destruction compared to the conventional heat storage systems. The system centers around parabolic trough solar collectors (PTCs). While power generation is achieved via an organic Rankine cycle (ORC) using toluene as the working fluid, freshwater is produced using a multi-stage flash (MSF) desalination unit. A key innovation is the incorporation of a cascaded thermal energy storage (TES) system with phase change materials. The present TES system features three modules operating at distinct temperature levels which are high: 200–225 °C for power generation, medium: 150–175 °C for desalination, and low: 80–90 °C for greenhouse thermal management, enabling synchronized energy storage and discharge to compensate for solar intermittency and meet varying demands. Thermodynamic performance is assessed using energy and exergy analyses. The results indicate that system outputs (electricity, heat, and freshwater) scale linearly with the PTC area, demonstrating predictable performance and modularity. For example, a 10,000 m 2 PTC area can yield approximately 77 m 3 of freshwater daily. The overall system maintains stable energy (19.4 %) and exergy (12.5 %) efficiencies across tested scales, though the difference highlights potential for optimization by minimizing thermodynamic irreversibilities. The TES system offered in this study enhances exergy efficiencies by 3.62 %. The integrated TES is crucial for extending operational hours, ensuring consistent resource production beyond direct solar availability. This integrated approach offers a robust solution for enhancing resource and food security and sustainability in arid environments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".