Proceedings of FOCAPD 2024ISSN: 2818-4734
Volume: 3 (2024)
LAPSE:2024.1624
Published Article
LAPSE:2024.1624
Designing Reverse Electrodialysis Process for Salinity Gradient Power Generation via Disjunctive Programming
Carolina Tristán, Marcos Fallanza, Raquel Ibáñez, Ignacio E. Grossmann, David Bernal Neira
August 16, 2024. Originally submitted on July 9, 2024
Reverse electrodialysis (RED) is a nascent renewable technology that generates clean, baseload electricity from salinity differences between two water streams, a renewable source known as salinity gradient energy (SGE). Full-scale RED progress calls for robust techno-economic and environmental assessments. Using generalized disjunctive programming (GDP) and life cycle assessment (LCA) principles, this work proposes cost-optimal and sustainable RED process designs involving different RED stack sizes and width-over-length ratios to guide the design and operation from the demonstration to full-scale phases. Results indicate that RED units will benefit from larger aspect ratios with a relative increase in net power of over 30% with 6 m2 membrane size. Commercial RED unit sizes (0.25–3 m2) require larger aspect ratios to reach an equal relative increase in net power but exhibit higher power densities. The GDP model devises profitable RED process designs for all the assessed aspect ratios in a foreseeable scenario for full-scale deployment, that is, the energy recovery from desalination concentrates mixed with reclaimed wastewater effluents. A RED system with 3 m2 RED units nine times wider than its length could earn a net present value of $2M at a competitive levelized cost of electricity of $111/MWh in the Spanish electricity market. On-site, RED-based electricity could abate roughly 7% of the greenhouse gas emissions from the desalination plant's energy supply, given the low emissions contribution of RED supply share. These findings demonstrate that optimization-based eco-technoeconomic assessments are a vital ally in making RED a full-scale reality.
Keywords
Life Cycle Analysis, Modelling and Simulations, Optimization, Process Design, Pyomo, Renewable and Sustainable Energy
Suggested Citation
Tristán C, Fallanza M, Ibáñez R, Grossmann IE, Neira DB. Designing Reverse Electrodialysis Process for Salinity Gradient Power Generation via Disjunctive Programming. Systems and Control Transactions 3:904-911 (2024) https://doi.org/10.69997/sct.126079
Author Affiliations
Tristán C: Purdue University, Davidson School of Chemical Engineering, West Lafayette, IN, USA
Fallanza M: University of Cantabria, Department of Chemical and Biomolecular Engineering, Santander, Spain
Ibáñez R: University of Cantabria, Department of Chemical and Biomolecular Engineering, Santander, Spain
Grossmann IE: Carnegie Mellon University, Department of Chemical Engineering, Pittsburgh, PA, USA
Neira DB: Purdue University, Davidson School of Chemical Engineering, West Lafayette, IN, USA; Universities Space Research Association, Research Institute of Advanced Computer Science, Mountain View, CA, USA; Quantum Artificial Intelligence Laboratory, NASA Ames Re
Journal Name
Systems and Control Transactions
Volume
3
First Page
904
Last Page
911
Year
2024
Publication Date
2024-07-10
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DOI Assigned
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PII: 0904-0911-676672-SCT-3-2024, Publication Type: Journal Article
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LAPSE:2024.1624
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https://doi.org/10.69997/sct.126079
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