MINLP based superstructure optimization for boron removal during desalination by reverse osmosis

• MINLP optimisation framework for boron removal in desalination is presented.
• Boron permeation is described using solution diffusion and thin film theories.
• Double pass superstructure of RO network is developed including SW pass and BW pass.
• For fixed freshwater demand and quality network design and operation are obtained.
• Effect of seawater temperature and pH on the design and operation are investigated.

In this work, a model based MINLP (mixed integer nonlinear programming) optimisation framework is developed for evaluating boron rejection in a reverse osmosis (RO) desalination process. A mathematical model (for the RO process) based on solution diffusion model and thin film theory is incorporated in the optimisation framework. A superstructure of the RO network is developed which includes two passes: (a) seawater pass containing normal two-stage RO system housing seawater membrane modules and (b) the brackish water pass (BW) accommodating brackish water membrane modules. For fixed freshwater demand, the objective of this work is to demonstrate the effectiveness of the MINLP approach for analyzing and optimizing the design and operation of RO network while attaining desired limit on boron concentration in the freshwater produced. The effect of seasonal variation in seawater temperature and pH on boron removal efficiency is also discussed.