Practical Implementation of a Hydro Power Unit Active Power Regulation Based on an MPC Algorithm

Traditionally, proportional-integral-derivative (PID) based hydro turbine governors are mainly used due to their robustness and simple implementation. However, the weakness of these controllers is their design based on linear models and fixed parameters structure. This implies that the controller's parameters are usually calculated for the critical operating point leading to the controller's underperformance when operating away from the critical operating point. This paper introduces a Model Predictive Control (MPC) based hydro turbine's governor load/frequency controller whose linear prediction model parameters are updated depending on the operating point. The main intention of the paper is to reduce the gap between theoretical contributions and industrial practice. The experimental validation is achieved by implementing the introduced MPC algorithm to a laboratory hydro power plant's governor Programmable Logic Controller (PLC) and comparing its response with the responses of the gain-scheduled PI (GS-PI) controller, PI controller based on Particle Swarm Optimization (PSO-PI) and the controller based on exponential control law (EXP).