Model predictive control in hydro turbine power control : doctoral thesis - Beus, Mateo (M. Beus, Faculty of electrical engineering and computing, 2021)
controllers. The main weakness of classical controllers is their design based on a linear plant model and a fixed parameter scheme. This means that a classical controller can perform optimally only at the operating point chosen during the controller design. However, hydro power plants are highly nonlinear systems, thus alternative control approaches based on adaptive parameters are needed. This research investigates the possibility of applying model predictive controller (MPC) as the load/frequency controller in hydro turbine governors. In the first part of the research the MPC algorithm is validated on the nonlinear simulation model of a laboratory hydro power plant, while in the second part of the research the MPC controller is implemented on a programmable logic controller that is used as a hydro turbine governor in the hydro power plant available in the Smart Grid laboratory at the University of Zagreb Faculty of Electrical Engineering and Computing. Furthermore, MPC controller behavior and practical implementation potential are validated for different operating conditions. Scientific contribution of the thesis consists of the following: - Model predictive control algorithm for a load/frequency controller of a hydro turbine governor - Methodology for real-time implementation of model predictive control algorithm using programmable logic controller, as well as an evaluation of MPC algorithm’s practical implementation potential for a load/frequency controller of a hydro turbine governor