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Data-driven optimization of two novel geothermal-powered systems integrating LNG regasification with thermoelectric generation for eco-friendly seawater desalination and data center cooling

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  • Mehrenjani, Javad Rezazadeh
  • Shirzad, Amirali
  • Adouli, Arman
  • Gharehghani, Ayat

Abstract

This study investigates the optimization of two innovative geothermal-powered multigeneration systems, each designed to simultaneously produce electricity, desalinated water, and cooling. Both systems integrate organic Rankine cycles (ORCs), absorption refrigeration cycles (ARCs), reverse osmosis (RO) desalination, liquefie.d natural gas (LNG) regasification, and thermoelectric generators (TEGs). The key distinction between the systems lies in the arrangement and working fluids of the ORCs: System 1 adopts a cascaded ORC configuration using ammonia and ethane, with the LNG-TEG serving as a heat sink for the cascaded ORC. In contrast, System 2 employs a sequential ORC design using isopentane and CO2, where the LNG-TEG functions as a heat sink for the low-temperature CO2-based ORC. These configurations influence system performance, with System 1 prioritizing freshwater and electricity production, and System 2 enhancing cooling capacity. Mathematical modeling, coupled with artificial neural networks (ANNs), facilitates multi-objective optimization using genetic algorithms. Two scenarios are explored: maximizing freshwater output in System 1 and improving cooling efficiency in System 2. The results reveal that System 1, under optimal conditions, achieves a desalination capacity of 32,488 m3/day, making it suitable for freshwater and electricity-intensive applications. In contrast, System 2 produces 24.65 MW of cooling, ideal for high-cooling-demand environments such as data centers. The analysis underscores a trade-off between initial investment and the levelized cost of electricity (LCOE). System 1, despite a higher upfront cost, offers a lower LCOE, while System 2 provides more immediate cost-effectiveness. This research advances the understanding of geothermal-powered systems, offering insights into their environmental sustainability and economic viability.

Suggested Citation

  • Mehrenjani, Javad Rezazadeh & Shirzad, Amirali & Adouli, Arman & Gharehghani, Ayat, 2024. "Data-driven optimization of two novel geothermal-powered systems integrating LNG regasification with thermoelectric generation for eco-friendly seawater desalination and data center cooling," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224036247
    DOI: 10.1016/j.energy.2024.133846
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    2. Hoseinzadeh, Siamak & Norouzi, Mohammad & Rezaie, Kianoosh & Hadi Ghasemi, M. & Astiaso Garcia, Davide, 2025. "Hybrid energy system for reverse osmosis desalination: Kalina cycle power from an abandoned oil well with hydrogen and battery backup during geothermal well maintenance," Energy, Elsevier, vol. 330(C).
    3. Yilmaz, Fatih & Ozturk, Murat & Selbas, Resat, 2025. "Proposal of an advanced hybrid multigeneration plant using solar energy for sustainable hydrogen generation: A thermodynamic and environmental analysis," Renewable Energy, Elsevier, vol. 243(C).
    4. Korpeh, Mobin & Lotfollahi, Amirhosein & Navid Faraji, S. & Gharehghani, Ayat & Ahmadi, Samareh, 2025. "Machine learning-assisted optimization of a novel hybrid solar-geothermal system supported by proton exchange membrane fuel cell for sustainable and continuous energy supply," Renewable Energy, Elsevier, vol. 247(C).

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