In this work, we propose an optimal control strategy as the unit control for combined-cycle power generation units. Using the same optimal control, we propose to optimize other internal control structures. Data-Enabled Predictive Control is chosen as the optimal control problem formulation, as it does not require a parametric state-space representation of the system. This bypasses the challenging and expensive-to-solve issue of parametric modeling and linearization for highly nonlinear systems. The performance of the controller is investigated in several critical operational scenarios, such as load-following for frequency control and disturbance rejection. Simulation results in Apros®, which is an environment dedicated to advanced process simulation, are presented.     «

In this work, we propose an optimal control strategy as the unit control for combined-cycle power generation units. Using the same optimal control, we propose to optimize other internal control structures. Data-Enabled Predictive Control is chosen as the optimal control problem formulation, as it does not require a parametric state-space representation of the system. This bypasses the challenging and expensive-to-solve issue of parametric modeling and linearization for highly nonlinear systems....     »