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Record W4412108750 · doi:10.1016/j.seta.2025.104443

Solar-driven multigeneration systems in grid-connected scheme integrated with air energy storage systems

2025· article· en· W4412108750 on OpenAlexaff
Farbod Esmaeilion, M. Soltani, Davide Astiaso Garcia

Bibliographic record

VenueSustainable Energy Technologies and Assessments · 2025
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Exergetic Analyses of Power and Cooling Systems
Canadian institutionsBalsillie School of International AffairsUniversity of Waterloo
Fundersnot available
KeywordsEnergy storageGridScheme (mathematics)Solar energyPhotovoltaic systemComputer scienceAerospace engineeringEnvironmental scienceEngineeringElectrical engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

As the world transfers toward a sustainable energy future, the need for efficient and reliable energy storage solutions has never been greater. This study explores integrating solar-driven multigeneration systems with air energy storage systems (AESS) in grid-connected settings, addressing the concerns posed by the intermittency of renewable energy sources. By capturing surplus solar energy and storing it for later use, AESS enhances grid stability, improves energy reliability, and reduces dependence on fossil fuels. Through a comprehensive analysis of thermodynamic, economic, and environmental factors, this research highlights the potential benefits of AESS, including improved round-trip efficiency and reduced greenhouse gas emissions. However, challenges such as energy losses during storage and retrieval and cost constraints remain key considerations. By bridging these gaps, this study elaborates the ongoing development of sustainable energy solutions, provided that valuable insights into the future of integrated renewable energy systems.

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.

How this classification was reachedexpand

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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