摘要：AbstractDue to ever-challenging global market conditions, plant economic optimization is becoming more critical. Recent advances have transformed the traditional steady-state real-time optimization (RTO) system of plant economic optimization to dynamic real-time optimization (DRTO) based on a dynamic prediction model. DRTO strategies that have been proposed perform economic optimization in an open-loop fashion without taking into account the presence of the plant control system. In this work, we propose a bilevel programming formulation for DRTO that includes effects of the closed-loop dynamics of an underlying constrained model predictive controller (MPC). The bilevel program is subsequently reformulated and solved as a single-level mathematical program with complementarity constraints (MPCC). We investigate the economics and control performance of the proposed strategy under varying MPC controller design parameters, and compare them to open-loop DRTO and rigorous multilevel closed-loop DRTO approaches.
