A Superstructure Based Optimization Approach for Regeneration Reuse of Water Network: Optimal Design of a Detailed Nanofiltration Regenerator Network

Abstract

Increasing freshwater costs and environmental concerns have necessitated the adoption of strategies for reducing freshwater consumption and effluent water discharge in chemical processes. Regeneration technologies increase opportunities for water reuse and recycle, and nanofiltration has emerged as a competitive wastewater regeneration technology. However, the optimal design of nanofiltration networks has not been extensively investigated. This study presents a framework for the optimal design and synthesis of multicontaminant nanofiltration membrane regenerator networks for application in water minimization problems. Mathematical optimization technique is developed based on a superstructure containing all system components and streams, incorporating nanofiltration units, pumps, and energy recovery devices. A linear approach and the modified Spiegler-Kedem model are explored in modelling the nanofiltration, and the steric-hindrance pore model is used to characterize the membrane. The objective of the optimization is to simultaneously minimize the water consumption and the total annual cost of the network. Furthermore, the optimal size, configuration, membrane properties and operating conditions of the equipment are determined. The applicability of the model is illustrated using a case study of an integrated pulp and paper plant. It was found that detailed models with customized modules are more useful when compared to the linear “black box” approach and approaches using fixed module specifications. The customized, detailed design of the regenerator network increased freshwater savings by 24% when compared to a black-box model, 31% when compared to a detailed model with fixed module specifications and 41% when compared to a reuse-recycle system with no regeneration. Similarly, cost savings of 38, 35 and 36% respectively were obtained. A trade-off was noted between the energy costs and the other components of the objective function since more energy was required to facilitate the reduction of water consumption and capital requirements.