An experimental optimization-based control strategy was developed and experimentally implemented on a reverse osmosis (RO) membrane desalination system. First, a dynamic non-linear model of the system was derived using mass and energy balances. Next, this model was combined with a model for system specific energy consumption. After the model parameters were fit using experimental system step-test data, the controller was implemented on the system. During the system operation, sensor data and user defined set-points were sent from the RO system user interface to the optimization code. In this code, the energy-optimal set-points for retentate valve position and feed flow rate were determined for the specified permeate flow rate. These set-points were then transmitted back to the RO system interface; the optimal feed flow rate value was then implemented as a set-point in the PI controller on the variable frequency drives, and the optimal retentate valve position was applied to the actuated retentate valve. The controller was shown to achieve energy usage values very close to the theoretically predicted values. It was also found that the salt rejection of the RO system decreased with increasing recovery (at a constant permeate flow rate); this issue can impose an additional constraint on the system operation. Future research plans in this area include comparison of the energy optimal modelbased controller to traditional reverse osmosis system controls in the presence of various disturbances; including permeate quality constraints.
This presentation is available to AMTA Members only.
- Alex Bartman
- University of California Los Angeles (UCLA)
- AMTA Annual Meeting, San Diego, CA
- San Diego Biennial
- Reverse Osmosis, Deminerlization, Non-linear model