Artificial neural Network-Based LCOH estimation for concentrated solar power plants for industrial process heating applications

AIT LAHOUSSINE OUALI, Hanane; TOUILI, Samir; ALAMI MERROUNI, Ahmed; MOUKHTAR, Ibrahim

doi:10.1016/j.applthermaleng.2023.121810

Cited by 5 publications

(6 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This equation is widely used to predict the convective heat transfer coefficient in turbulent flow within tubes. The heat transfer coefficient (ℎ) is then calculated from the Nusselt number using the relationship in Equation (2).…”

Section: Discussionmentioning

confidence: 99%

“…The heat transfer coefficient (h) is then calculated from the Nusselt number using the relationship in Equation (2).…”

Section: Discussionmentioning

confidence: 99%

“…They enhance the thermal conductivity of base fluids by incorporating nanoparticles made from metals, metal oxides, or carbon-based materials. This enhancement is due not only to the high conductivity of the nanoparticles but also to the increased chaotic particle 2 of 24 displacement (Brownian motion) and the formation of thermally conductive layers at the fluid-particle interfaces [2].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhancement in Turbulent Convective Heat Transfer Using Silver Nanofluids: Impact of Citrate, Lipoic Acid, and Silica Coatings

Bunpheng,

Dhairiyasamy

2024

ChemEngineering

View full text Add to dashboard Cite

This study aims to investigate the thermohydraulic performance of silver nanofluids with different surface modifications (citrate, lipoic acid, and silica) in turbulent convective heat transfer applications. Three silver nanofluids were prepared, each modified with citrate, lipoic acid, or silica coatings. The nanofluids were characterized for stability using zeta potential measurements and evaluated in a smooth brass tube under turbulent flow conditions. The experimental setup involved measuring the temperature, pressure, and flow rate to assess heat transfer coefficients, pressure drops, and friction factors. The results were compared with distilled water as the base fluid and validated against theoretical models. The silica-shelled nanofluid (Ag/S) exhibited a significant 35% increase in the average heat transfer coefficient compared to distilled water, while the citrate-coated (Ag/C) and lipoic acid-coated (Ag/L) nanofluids showed slight decreases of approximately 0.2% and 2%, respectively. The Ag/S nanofluid demonstrated a 9% increase in the mean Nusselt number, indicating enhanced heat transfer capabilities. However, all modified nanofluids experienced higher pressure drops and friction factors than the base fluid, with the Ag/S nanofluid showing the highest increase in viscosity (11.9%). Surface modifications significantly influence the thermohydraulic performance of silver nanofluids. The silica-shelled nanofluid shows the most substantial enhancement in heat transfer, making it a promising candidate for applications requiring efficient thermal management. However, the increased hydraulic costs associated with higher-pressure drops and friction factors must be carefully managed. Further research is needed to optimize these nanofluids for specific industrial applications, considering long-term stability and the effects of different nanoparticle concentrations and geometries.

show abstract

Section: Discussionmentioning

confidence: 99%

“…The heat transfer coefficient (h) is then calculated from the Nusselt number using the relationship in Equation (2).…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancement in Turbulent Convective Heat Transfer Using Silver Nanofluids: Impact of Citrate, Lipoic Acid, and Silica Coatings

Bunpheng,

Dhairiyasamy

2024

ChemEngineering

View full text Add to dashboard Cite

show abstract

“…Utilizing data from Table , they stress the importance of conducting an economic analysis of wind power-based hydrogen production through the Green Index (GI) and the Levelized Cost of Hydrogen (LCOH). The GI represents the percentage of renewable energy used to produce a unit of hydrogen, while the LCOH serves as a tool to assess the total cost of heat energy generated by the system over its entire lifespan, encompassing factors such as initial investment and fuel costs, operational expenses, maintenance fees, and the expected lifespan of the system . The results indicate that the system can achieve a GI of 94% with an emission intensity of 235 kgCO 2 /tls (tons of liquid steel), while LCOH reaches approximately 6.5 €/kg …”

Section: The Raw Materials Of E-fuelsmentioning

confidence: 99%

“…The GI represents the percentage of renewable energy used to produce a unit of hydrogen, 38 while the LCOH serves as a tool to assess the total cost of heat energy generated by the system over its entire lifespan, encompassing factors such as initial investment and fuel costs, operational expenses, maintenance fees, and the expected lifespan of the system. 39 The results indicate that the system can achieve a GI of 94% with an emission intensity of 235 kgCO 2 /tls (tons of liquid steel), while LCOH reaches approximately 6.5 €/kg. 40 Mohammad Ali Abdelkareem et al have comprehensively outlined the general routes for commercially available solar energy-based hydrogen production.…”

mentioning

confidence: 91%

Perspectives and Outlook of E-fuels: Production, Cost Effectiveness, and Applications

Shi,

Guan,

Zhuang

et al. 2024

Energy Fuels

View full text Add to dashboard Cite

With the introduction of the EU's "ban on combustion" proposal in 2035, the sale of new fossil fuel vehicles will soon be comprehensively prohibited. The use of e-fuels has become the best means for the survival and continuation of internal combustion engines, while also responding to the call for carbon neutrality. This review studies how the raw materials required for different e-fuels can be obtained through the assistance of renewable energy or various net-zero carbon emission routes, and elaborates on the synthesis methods, economics, and challenges faced by e-fuels such as e-methanol and e-ammonia. E-fuels have a wide range of market applications, including but not limited to road transportation, aviation, and shipping, and some transportation vehicles have already chosen e-fuels as their fuel. By summarizing the technoeconomic analysis of e-fuels, this review aims to provide referable methods and multiple options for the future large-scale production of e-fuels, as well as insights for the subsequent application and improvement of e-fuels.

show abstract

Toward a sustainable dairy industry in Mexico: optimization of a parabolic trough solar collector system with passive heat-transfer enhancement techniques and a machine learning approach

Cetina-Quiñones,

Bassam,

Carrillo

et al. 2024

Environ Dev Sustain

View full text Add to dashboard Cite

Artificial neural Network-Based LCOH estimation for concentrated solar power plants for industrial process heating applications

Cited by 5 publications

References 47 publications

Enhancement in Turbulent Convective Heat Transfer Using Silver Nanofluids: Impact of Citrate, Lipoic Acid, and Silica Coatings

Enhancement in Turbulent Convective Heat Transfer Using Silver Nanofluids: Impact of Citrate, Lipoic Acid, and Silica Coatings

Perspectives and Outlook of E-fuels: Production, Cost Effectiveness, and Applications

Toward a sustainable dairy industry in Mexico: optimization of a parabolic trough solar collector system with passive heat-transfer enhancement techniques and a machine learning approach

Contact Info

Product

Resources

About