Integration of Real-Time Optimization and Model-Predictive Control: Application to Refinery Processes

This article presents the application of integrating real-time optimization with model-predictive control on a hydrocracking unit on a model case refinery in the Middle East. Real-time optimization (RTO) provides technological excellence that helps to maximize the contribution of the plant to the business profit, provides best-in-class performance, optimizing the plant operation, enhancing safety and reliability. The main objective of RTO implementation on refinery processes was to optimize the operation by applying online rigorous nonlinear closed-loop optimization technology. RTO contributed to optimize key process operating variables by shifting the unit margin toward the optimum, and operation was better placed to challenge targets and operating conditions, driving the plant toward a more profitable operating regime and bringing the higher benefits. The steady-state and kinetic models were developed and used by RTO to improve the yield of high value products by maximizing the economic objective function to enhance the yields of diesel and gasoline. Increasing the feed rate subject to unit constraints and catalyst run length was another objective of RTO implementation. In addition, potential RTO applications have been highlighted in this article for achieving CO2 emission reduction using two different approaches: improvement of energy efficiency and application of CO2 capture and conversion technologies. This application will integrate model predictive control (MPC) with RTO with an ultimate aim to maximize an economic objective function to reduce CO2 emission.