Optimization in reverse osmosis plants through risk mitigation

This paper introduces a risk-based method to optimize the production of water treatment plants. Risk factors such as demands, operating and maintenance cost or power cost are considered in the optimization to satisfy the product quality and demands, depending on the season. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to determine the set of mitigation actions to be executed. The model of the plant has been obtained from simulation by considering a commercial membrane from Dow company. Different simulations are executed to illustrated the benefits of the proposal.