Predicting reverse electrodialysis performance in the presence of divalent ions for renewable energy generation. (1st September 2021)

• Record Type: Journal Article
• Authors: Pintossi, Diego; Simões, Catarina; Saakes, Michel; Borneman, Zandrie; Nijmeijer, Kitty
• Is Part Of: Energy conversion and management. Volume 243(2021)
• Publication Date: 2021-09-01
• Subjects: Reverse electrodialysis -- Fouling -- Sulfate -- Magnesium -- Uphill transport -- Model; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2021.114369
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Highlights: Novel reverse electrodialysis process model including magnesium and sulfate. Uphill transport, increased membrane resistance, and permselectivity loss included. Model validation with experimental data and literature data (up to 50 mol. %). Model reproduces RED in single-stage, multi-stage, and segmented electrode. Abstract: Reverse electrodialysis (RED) is an electro-membrane process to harvest renewable energy from salinity gradients. RED process models have been developed in the past, but they mostly assume that only NaCl is present in the feedwaters, which results in unrealistically high predictions. In the present work, an existing simple model is extended to accommodate the presence of magnesium ions and sulfate in the feedwaters, and potentially even more complex mixtures. All power loss mechanisms deriving from the presence of multivalent ions are included in the new model: increased membrane electrical resistance, uphill transport of multivalent ions from the river to the seawater compartment, and membrane permselectivity loss. This new model is validated with experimental and literature data of membrane electrical resistance (at 10 mol. % MgCl2 for the CEMs and 25 mol. % Na2 SO4 for the AEMs), RED stack performance (up to 50 mol. % MgCl2 or Na2 SO4 in the feedwaters), and ion transport (at 10 mol. % MgCl2 or Na2 SO4 in the feedwaters) showing very good agreement between model predictions and experimental data. Finally, we showed that the developed model not only describes experimental data but can also predict RED performances under a variety of conditions and cross-flow configurations (single-stage with and without electrode segmentation, multi-stage in co-current and counter-current mode) and feedwater compositions (only NaCl, with Na2 SO4, with MgCl2, and with MgSO4 ). It thus provides a very valuable tool to design and evaluate RED process systems.