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

Abstract

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 RU process) based on solution diffusion model and thin film theory is incorporated in the optimisation framework. A superstructure of the RU network is developed which includes two passes: (a) seawater pass containing normal two-stage RU 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 RU 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.