Evidence map›Paper›PMID 40596586›Full record

ArticleScientific reports2025

Techno-economic optimization of hybrid renewable systems for sustainable energy solutions.

Kanaga Bharathi N, Manoharan Abirami, Devi Vighneshwari, Manoharan Hariprasath

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kanaga Bharathi NResearch Scholar, Department of Electrical Engineering, Annamalai University, Chidambaram, Tamil Nadu, India. bharathi.nagesh@gmail.com.
Manoharan AbiramiDepartment of Electrical Engineering, Annamalai University, Chidambaram, Tamil Nadu, India.
Devi VighneshwariDepartment of Electrical and Electronics Engineering, The Oxford College of Engineering, Bengaluru, Karnataka, India.
Manoharan HariprasathDepartment of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study is focusing on the techno-economic optimization of hybrid renewable energy systems and the energy. The system integrates geothermal, wind, and solar sources for sustainable hydrogen production its important. The objective is to maximize energy efficiency, reduce operational costs, and ensure stable energy delivering. A simulation-based framework is used for analyse system behaviour under various environmental conditions it helps. The scope includes defining parameter, sensitivity analysis, and optimization using iterative algorithms which are complex. Time-step simulations evaluating energy dynamics help to and performance trade-offs, which is necessary for understanding. The proposed hybrid system achieves 78.5% energy efficiency and 64.3% exergy efficiency, and this is good. It produces 500 kg of hydrogen daily with an LCOE of $0.085 per kWh, which is quite low. Sensitivity results show that a 15% increase in wind speed improves output by 10%, and this is significant. A 20% drop in solar irradiance reduces output by 8%, which is not good. Geothermal contributes 40% of the total energy share, with wind and solar supplying 35% and 25%, respectively, and this shows balance. Optimization improves hydrogen production efficiency by 12% and leads to a six-year payback period, which is reasonable. The system shows resilience under load changes, supporting its robustness that is impressive. The findings validate the system's scalability and economic potential, which is promising for future. Future work will explore advanced storage and real-time adaptive control.

Indexed as

Energy efficiencyExergy efficiencyHybrid renewable energy systemsHydrogen productionLevelized cost of energySustainabilityTechno-economic optimization

Identifiers

PMID40596586
PMCPMC12219102

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.