Efficient NMPC strategies for thermal stress control of steam turbines

This paper proposes an advanced control strategy for steam turbines characterized by frequent load variations based on a nonlinear model predictive control (NMPC) algorithm. In this specific scenario, turbines are subject to frequent variations in operating conditions and repeated start-ups that cause significant thermal stress. The main purpose of the developed NMPCs is to effectively regulate the generated electric power while limiting the rotor thermal stress. Collocation methods are adopted to improve the computation time required to solve the optimal control problem and then compared with a standard multiple-shooting approach. The proposed formulation includes time-varying constraints and nonlinear disturbances that vary within the prediction horizon of the dynamic module of the controller.