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Record W4402737734 · doi:10.1016/j.tsep.2024.102922

A unique solar pond system integrated with chlor-alkali electrolyser for heat storage and hydrogen production

2024· article· en· W4402737734 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThermal Science and Engineering Progress · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsHydrogen productionHydrogen storageEnvironmental scienceProduction (economics)Alkali metalThermal energy storageProcess engineeringNuclear engineeringWaste managementHydrogenChemistryEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

• 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 In order to produce hydrogen, the saline water withdrawn from the upper convective zone is used in a chlor-alkali electrolyser powered by solar PV in order to produce green hydrogen.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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.206
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it