Development of a geothermal-driven multi-output scheme for electricity, cooling, and hydrogen production: Techno-economic assessment and genetic algorithm-based optimization Article Swipe
Xiaoming Guo
,
Azher M. Abed
,
Mohammed A. Alghassab
,
Fahad M. Alhomayani
,
Ibrahim Mahariq
,
Yasser Elmasry
,
Mohammad Safi
,
Fahad Alturise
,
Salem Alkhalaf
,
Albara Ibrahim Alrawashdeh
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2024.105228
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2024.105228
This study aims to develop an environmentally friendly multi-energy system for sustainable production of electricity, cooling and hydrogen. The study introduces a pioneering geothermal-based system, integrating an ejector refrigeration cycle, a dual-loop organic Rankine cycle, and a hydrogen production unit with proton exchange membrane electrolyzers. The study provides a thorough analysis of the system's energy and exergy performance, as well as its economic feasibility. Through sensitivity and parametric analyses, the research identifies key parameters that significantly influence system performance. The system's innovative design promises minimal environmental impact while delivering multifaceted performance: generating 1.38 MW of electricity, supplying 436 kW of cooling load, and producing 5.39 kg/h of hydrogen. In the exergy analysis, Evaporator1 is identified as the primary contributor to exergy loss, representing 34 % of the total exergy destruction. This is followed by the electrolysis unit, the condenser, and the ejector refrigeration cycle, which contribute 18 %, 14 %, and 12 %, respectively. The system achieves optimal efficiency at an organic Rankine cycle turbine1 inlet temperature of 387 K, yielding a power generation of 885.4 kW and an exergy efficiency of 26.7 %. Beyond this temperature, any further increase leads to a decline in power output due to operational disturbances. A multi-criteria optimization using genetic algorithm is applied, resulting in an optimized system with a cost rate of 18.13 $/h and an exergy efficiency of 38.96 %.
Related Topics
Concepts
Production (economics)
Hydrogen production
Geothermal gradient
Scheme (mathematics)
Electricity
Computer science
Genetic algorithm
Mathematical optimization
Algorithm
Hydrogen
Process engineering
Environmental science
Economics
Chemistry
Electrical engineering
Geology
Mathematics
Engineering
Macroeconomics
Organic chemistry
Geophysics
Mathematical analysis
Machine learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.csite.2024.105228
- OA Status
- gold
- Cited By
- 4
- References
- 68
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403151063
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403151063Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.csite.2024.105228Digital Object Identifier
- Title
-
Development of a geothermal-driven multi-output scheme for electricity, cooling, and hydrogen production: Techno-economic assessment and genetic algorithm-based optimizationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-05Full publication date if available
- Authors
-
Xiaoming Guo, Azher M. Abed, Mohammed A. Alghassab, Fahad M. Alhomayani, Ibrahim Mahariq, Yasser Elmasry, Mohammad Safi, Fahad Alturise, Salem Alkhalaf, Albara Ibrahim AlrawashdehList of authors in order
- Landing page
-
https://doi.org/10.1016/j.csite.2024.105228Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.csite.2024.105228Direct OA link when available
- Concepts
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Production (economics), Hydrogen production, Geothermal gradient, Scheme (mathematics), Electricity, Computer science, Genetic algorithm, Mathematical optimization, Algorithm, Hydrogen, Process engineering, Environmental science, Economics, Chemistry, Electrical engineering, Geology, Mathematics, Engineering, Macroeconomics, Organic chemistry, Geophysics, Mathematical analysis, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4Per-year citation counts (last 5 years)
- References (count)
-
68Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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