A unique solar pond system integrated with chlor-alkali electrolyser for heat storage and hydrogen production
Bibliographic record
Abstract
• A solar pond integrated with a chlor-alkali electrolyser is developed. • A chlor-alkali electrolyser is included to benefit from the rejected saline from the pond. • A system performance assessment is performed using multiple criteria. • The overall energy and exergy efficiencies appear to be appealing. Solar ponds are recognized as a simple, but a unique solution for renewable heat storage to use later. A freshwater feed to solar ponds is considered a crucial requirement to maintain the salinity gradient accordingly for heat storage purposes. This study aims to benefit from this specific requirement for solar ponds by integrating chlor-alkali electrolysers to produce hydrogen along with heat storage, which is a common purpose of a solar pond. Therefore, the proposed system establishes a desirable synergy, as per the sustainable development goals, between a conventional solar pond and an innovative high-tech hydrogen production system. In order to produce hydrogen, the saline water withdrawn from the upper convective zone is used in a chlor-alkali electrolyser powered by solar PV in order to produce green hydrogen. Thus, a conventional solar pond is converted into an integrated energy system that produces hydrogen and chlorine for useful purposes, along with heat storage capability. The system’s performance has been assessed in terms of the energy and exergy efficiencies for five distinct cities located in different countries that are grappling with poverty. The system’s performance, which is assessed in five cities, demonstrates the energy and exergy efficiencies ranging from 11.66 % to 14.56 % and 6.84 % to 8.60 % for the solar pond. They vary from 21.95 % to 24.22 % and from 14.23 % to 14.66 % for the overall system, respectively. Furthermore, the system effectively captures and stores solar energy, and it reaches temperatures up to 89.1°C. Moreover, the proposed system is expected to contribute to the United Nations’ Sustainable Development Goals by addressing energy poverty, promoting clean energy, and fostering economic growth.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".