Optimum synthesis of an electrodialysis framework with a Background Process II: Optimization and synthesis of a water network

• Simultaneous minimization of energy and water in water network synthesis problem.
• Multi-contaminant electrodialysis design model embedded into water network.
• 38% savings in freshwater consumption for pulp and paper case study.
• Integrated approach results in 80% reduction in energy associated with regeneration.
• Up to 3.5% reduction in consumption and cost-compared to black box approach.

The water-energy nexus considers the relationship between water and energy resources. The tightening environmental regulations and social pressures have made it necessary to develop processes that are conservative with respect to both these resources. In the first part of this series, a multi-contaminant electrodialysis (ED) model was developed. In this second part of the series, the application of the developed ED model for the partial purification of contaminated water within a water network synthesis (WNS) and optimization problem is explored. The optimization model is based on a superstructure framework, where the objective is to minimize freshwater consumption, wastewater production, energy consumption and the operating and capital costs involved in the process integration. A comparison is made between the framework presented in this manuscript and the more common black box model, which simplifies regeneration units to linear expressions. The results show that the black box approach can lead to inaccuracies of up to 85% in the costing of regeneration units. ED optimization performed within the WNS problem results in a more comprehensive design than if the design is developed as a standalone model. Furthermore, it is shown that there are significant environmental and financial benefits in the simultaneous minimization of water and energy in water networks. When applied to a pulp and paper case study, the integrated approach resulted in 38% reduction in total freshwater consumption and 67% savings in wastewater treatment costs.