Parameter-based performance evaluation and optimization of a capacitive deionization desalination process

Abstract

Capacitive deionization (CDI) is an emerging alternative desalination technology that electrochemically purifies brackish water using electrically polarized capacitive electrodes. This research focuses on the performance of the CDI system. A number of performance criteria were used to assess the desalination system based on the requirements. The performance of the CDI system was assessed in terms of lowest effluent water concentration during the deionization process (mM), specific energy consumption either per gram of salt adsorbed (kJ/g) or per liter of fresh water recovered (J/L), accumulated desalinated water concentration (ppm), salt ions adsorbed in electrodes (g), and the volume of freshwater recovered (L) for different operating parameters. Furthermore, the performance of the desalination system was optimized based on operating parameters of flow rate, applied voltage, cell volume, and capacitance of the CDI cell. Three optimization techniques were suggested according to desalination requirements. Single-objective and multi-objective genetic algorithms (GA) were used to optimize the performance of the CDI system subject to constrained decision variables. The feasible solution obtained through GA optimization showed significant improvement in CDI system performance. Furthermore, the optimized results suggest different optimal solutions based on specific needs, such as maximum salt ion adsorption, lowest desalination energy consumption, high volume of desalinated water, or purest water extracted.