Designing Reverse Electrodialysis Process for Salinity Gradient Power Generation via Disjunctive Programming

Abstract

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.