Research on an improved model predictive control–based control strategy for a two-stage cascaded hydropower stations with a regulating reservoir

This paper proposes an improved model predictive control (IMPC) algorithm to address the complex control challenges presented by the specific topology of the grid-connected two-stage cascaded hydropower station with a regulating reservoir, including strong nonlinearity, significant inertia, and multiple constraints. The algorithm aims to enhance the system's power tracking performance, frequency stability, and hydraulic safety. First, a high-fidelity prediction model for the grid-connected model of the two-stage cascaded hydropower station with a regulating reservoir is established, providing a precise foundation for the predictive controller. Furthermore, a composite control architecture is developed based on the integration of IMPC and a Kalman filter algorithm. This architecture incorporates a nonlinear disturbance compensation mechanism, leading to the design of an advanced IMPC strategy. Finally, the effectiveness of the proposed controller is validated under various typical operating conditions, such as load step changes and continuous fluctuations. The results demonstrate that the improved IMPC controller exhibits significant advantages in control accuracy, response speed, operational smoothness, and robustness, while strictly satisfying all critical operational constraints. This study offers an effective new approach for addressing control problems in similar complex hydropower systems, holding considerable theoretical value and practical application prospects. In practical application.