Data-driven optimization of two novel geothermal-powered systems integrating LNG regasification with thermoelectric generation for eco-friendly seawater desalination and data center cooling
Javad Rezazadeh Mehrenjani,
Amirali Shirzad,
Arman Adouli and
Ayat Gharehghani
Energy, 2024, vol. 313, issue C
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.
Keywords: Geothermal-powered desalination; Data center cooling; Organic Rankine cycle; Reverse osmosis (RO) desalination; Multi-objective optimization; Artificial neural network (ANN) (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544224036247
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224036247
DOI: 10.1016/j.energy.2024.133846
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().