258491 Real-Time Operation and Control of Integrated Ultrafiltration-Reverse Osmosis Membrane Desalination System

Monday, October 29, 2012: 8:30 AM
306 (Convention Center )
Larry Gao, Chemical & Biomolecular Engineering, UCLA, Los Angeles, CA, Han Gu, Chemical & Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, Anditya Rahardianto, Institute of the Environment & Sustainability, UCLA, Los Angeles, CA, Panagiotis D. Christofides, Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA and Yoram Cohen, Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA

Reverse osmosis (RO) membrane desalination has emerged as one of the leading methods for water desalination due to the low cost and energy efficiency of the process.  Recent advances in model-based control and energy optimization for RO desalination [1-3] have made it possible to develop self-adaptive operational strategies for RO membrane desalination systems.  The goal of self-adaptive operation is to enable the plant to autonomously respond to changes in feed water  salinity and fouling propensity.  In order to combat membrane fouling, RO feed water pre-treatment is crucial for effective RO desalination. In recent years, microfiltration (MF) and ultrafiltration (UF) systems have been increasingly explored for effective feed-filtration. While the concept of UF/RO integration is appealing, there are significant technical challenges in situations where plant footprint (e.g., for shipboard desalination) is at a premium, the use of cleaning chemicals must be kept to a minimum, and feed water quality often fluctuates.  To demonstrate the feasibility of an integrated UF/RO system and the operational benefits of advanced process control, the UCLA team developed a compact second generation RO (CoM2RO) desalination system integrated with MF-UF feed filtration.  The CoM2RO implements two unique controllers:  a novel RO model-based controller capable of simultaneously self-adjusting the feed flow rate and trans-membrane pressure in order to maintain the desired water productivity and quality, and a self-adaptive UF operational strategy that varies backwashing intensity depending on detected fouling levels.  These controllers enable integration of the two systems such that the UF can directly utilize the RO concentrate for backwashing and minimizes RO energy consumption, while the RO system adapts to any changes in pressure, flow rate, or salinity that result from the cyclic nature of the UF backwashing.  Real-time sensors data along with embedded computing capability allow on-line membrane element characterization and overall system performance assessment (with appropriate data normalization) that are used for rapid control and optimization.  A field evaluation of the present advanced RO/UF system control was carried out for seawater desalination.  Experiments demonstrated that the pre-treatment operation significantly improved the RO feed water conditions (Turbidity, florescence reading, particle size) which the RO controller successfully adapted to while maintaining constant RO permeate production and quality.  Real-time sensor data allowed for on-line system characterization of fouling levels in the UF system, thereby enabling adjustment of operating conditions as well as fault detection and significantly lengthening the operational duration of the system.  Results of the study demonstrated that the real-time information regarding membrane characterization enabled fault detection and rapid evaluation of the impact of varying fouling and feed conditions on the performance of both UF and RO systems.  


  1. Zhu, A., P. D. Christofides and Y. Cohen, “Effect of Thermodynamic Restriction on Energy Cost Optimization of RO Membrane Water Desalination,” Industrial and Engineering Chemistry Research, 48, 6010-6021 (2009).
  2. Bartman, A.R., A.H. Zhu, P.D. Christofides, Y. Cohen, “Minimizing Energy Consumption in Reverse Osmosis Membrane Desalination using Optimization-Based Control,”  J. Process Control, 20, 1261-1269 (2010).
  3. Zhu, A., P. D. Christofides, and Y. Cohen, "Energy Consumption Optimization of Reverse Osmosis Membrane Water Desalination Subject to Feed Salinity Fluctuation," Ind. Eng. Chem Res, 48, 9581–9589(2009).

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