Solar-Enhanced ocean thermal energy conversion for green liquid hydrogen production

被引:0
作者
Wang, Lina [1 ]
Alirahmi, Seyed Mojtaba [2 ]
Rejeb, Oussama [3 ]
机构
[1] Dalian Ocean Univ, Sch Marine Technol & Environm, Dalian, Peoples R China
[2] Aalborg Univ, Dept Chem & Biosci, Esbjerg, Denmark
[3] Univ Pau & Pays Adour, Lab Sci Ingn Appl Mecan & Genie Elect SIAME, Pau, France
关键词
Liquid hydrogen; ORC; Working fluid selection; Multi-objective optimization; ANN; s-OTEC; ORGANIC RANKINE CYCLES; WASTE HEAT-RECOVERY; MULTIOBJECTIVE OPTIMIZATION; EXERGOECONOMIC ANALYSIS; MODEL VALIDATION; SYSTEM; POWER; TEMPERATURE; EXERGY; GAS;
D O I
10.1016/j.applthermaleng.2025.125615
中图分类号
O414.1 [热力学];
学科分类号
摘要
A design, simulation, and optimization of a solar-enhanced ocean thermal energy conversion system for the simultaneous production of power and liquid hydrogen are proposed. This study explores a novel approach to enhancing ocean thermal energy conversion performance by integrating solar thermal collectors with nanofluids, thereby augmenting the exergy efficiency and system economics. Incorporating solar thermal flat plate collectors with nanofluid as an additional heat source increased power generation through the organic Rankine cycle. EES software performs thermodynamic modeling, while data analysis uses artificial neural networks. The multiobjective grey wolf optimizer algorithm is enacted to ascertain the most advantageous operational parameters for the chosen working fluids of the organic Rankine cycle (R134a, R245fa, R290, and R600). The TOPSIS decision-making method was then applied to assess and contrast the performance of working fluids. The findings revealed that R245fa emerged as the supremely optimal working fluid, exhibiting the best performance among the options considered. It achieved a peak exergy efficiency of 12.62 % alongside a maximal mass flow rate of liquefied hydrogen production reaching 25.53 kg/h. The total investment rate is minimized to 383.38 $/h. The associated study offers a foundation for further investigating and commercializing ocean thermal energy conversion technology in the hydrogen energy sector.
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页数:13
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共 62 条
[1]   Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research [J].
Agatonovic-Kustrin, S ;
Beresford, R .
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2000, 22 (05) :717-727
[2]   Comparative performance analysis of low-temperature Organic Rankine Cycle (ORC) using pure and zeotropic working fluids [J].
Aghahosseini, S. ;
Dincer, I. .
APPLIED THERMAL ENGINEERING, 2013, 54 (01) :35-42
[3]   Parametric study and optimization of the precooled Linde-Hampson (PCLH) cycle for six different gases based on energy and exergy analysis [J].
Akhoundi, Mahla ;
Deymi-Dashtebayaz, Mahdi ;
Tayyeban, Edris ;
Khabbazi, Hossein .
CHEMICAL PAPERS, 2023, 77 (09) :5343-5356
[4]   Multi-objective optimization of regenerative ORC system integrated with thermoelectric generators for low-temperature waste heat recovery [J].
Aliahmadi, Mohammad ;
Moosavi, Ali ;
Sadrhosseini, Hani .
ENERGY REPORTS, 2021, 7 :300-313
[5]   An innovative four-objective dragonfly-inspired optimization algorithm for an efficient, green, and cost-effective waste heat recovery from SOFC [J].
Alirahmi, Seyed Mojtaba ;
Behzadi, Amirmohammad ;
Ahmadi, Pouria ;
Sadrizadeh, Sasan .
ENERGY, 2023, 263
[6]   Comparative study, working fluid selection, and optimal design of three systems for electricity and freshwater based on solid oxide fuel cell mover cycle [J].
Alirahmi, Seyed Mojtaba ;
Ebrahimi-Moghadam, Amir .
APPLIED ENERGY, 2022, 323
[7]   Soft computing analysis of a compressed air energy storage and SOFC system via different artificial neural network architecture and tri-objective grey wolf optimization [J].
Alirahmi, Seyed Mojtaba ;
Mousavi, Seyedeh Fateme ;
Ahmadi, Pouria ;
Arabkoohsar, Ahmad .
ENERGY, 2021, 236 (236)
[8]   Electrolyzer-fuel cell combination for grid peak load management in a geothermal power plant: Power to hydrogen and hydrogen to power conversion [J].
Alirahmi, Seyed Mojtaba ;
Assareh, Ehsanolah ;
Chitsaz, Ata ;
Holagh, Shahriyar Ghazanfari ;
Jalilinasrabady, Saeid .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2021, 46 (50) :25650-25665
[9]   A comprehensive techno-economic analysis and multi-criteria optimization of a compressed air energy storage (CAES) hybridized with solar and desalination units [J].
Alirahmi, Seyed Mojtaba ;
Mousavi, Shadi Bashiri ;
Razmi, Amir Reza ;
Ahmadi, Pouria .
ENERGY CONVERSION AND MANAGEMENT, 2021, 236
[10]   Energy, exergy, and exergoeconomics (3E) analysis and multi-objective optimization of a multi-generation energy system for day and night time power generation - Case study: Dezful city [J].
Alirahmi, Seyed Mojtaba ;
Assareh, Ehsanolah .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2020, 45 (56) :31555-31573