Cost-optimal design of reverse electrodialysis process for salinity gradient-based electricity generation in desalination plants

C. Tristán, M. Fallanza, I. Ortiz, R. Ibáñez and I.E. Grossmann

Energy, 2024, vol. 313, issue C

Abstract: Salinity gradient-based technologies offer a solution for desalination plants seeking clean, uninterrupted electricity to support their decarbonization and circularity. This work provides cost-optimal designs of a large-scale reverse electrodialysis (RED) system deployed in a desalination plant using mathematical programming. The optimization model determines the hydraulic topology and RED units' working conditions that maximize the net present value (NPV) of the RED process recovering salinity gradient energy between brine and treated wastewater effluents. We examine how electricity, carbon and membranes prices, desalination plant capacity, and membrane resistance may affect the NPV-optimal design's competitiveness and performance. We also compare the conventional series-parallel configuration and the NPV-optimal solution with recycling and added reuse alternatives. In the context of soaring electricity prices and strong green financing support, with the use of high-performing, affordable membranes (∼10 €/m2), RED could save 8 % of desalination plant energy demand from the grid, earning 5 M€ profits and LCOE of 66–126 €/MWh, comparable to other renewable and conventional power technologies. The optimization model finds profitable designs for the entire range of medium-capacity desalination plants. The findings underscore the optimization model effectiveness in streamlining decision-making and exploiting the synergies of full-scale, RED-based electricity in the energy-intensive water sector.

Keywords: Renewable energy; Generalized disjunctive programming; Reverse osmosis; Wastewater treatment; Water-energy nexus (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224037836

DOI: 10.1016/j.energy.2024.134005

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