Thermal Stress Control of Steam Turbines via Efficient NMPC Strategies

On October 7, we organized a scientific seminar on “Thermal Stress Control of Steam Turbines via Efficient Nmpc Strategies“. Riccardo Bacci di Capaci, an assistant professor at the University of Pisa, Italy, led the seminar, which was organized in the framework of the FrontSeat project as part of the seminar series on “Research Seminar on Smart Cybernetics.”

Abstract:
Steam turbines employed in modern power generation plants, such as concentrated solar plants or combined cycle power plants, are typically characterized by frequent load variations due to changes in site weather conditions or operation strategies (i.e., from base load to peak load follower). In such scenarios, these rotating machines prove subject to frequent variations in operating conditions and repeated start-ups that cause significant thermal stress, especially around the rotor shaft. This talk illustrates the design and implementation of an advanced control strategy based on a nonlinear model predictive control (NMPC) algorithm, which can regulate the generated electric power while limiting the rotor thermal stress. In particular, collocation methods are adopted to improve the computation time required to solve the optimal control problem. Hence, they are compared with two previous single-shooting approaches and a standard multiple-shooting method. The proposed NMPC formulation includes time-varying constraints and nonlinear disturbances that vary within the prediction horizon of the dynamic module of the controller. Extensive open-loop and closed-loop simulations show the effectiveness of the proposed methodologies.

This project has received funding from the European Union’s Horizon under grant no. 101079342 (Fostering Opportunities Towards Slovak Excellence in Advanced Control for Smart Industries).