Design of stochastic model predictive control for wind energy conversion system

This paper investigates an approach for Wind Energy Conversion System (WE CS) with model uncertainties and disturbances based on scenario tree Stochastic Model Predictive Control (SMPC). First, in order to describe the randomness of the system, the WECS's Markov jump model is formulated with the help of the statistical data of wind. Next, the uncertain stochastic model predictive control problem is transformed into deterministic Model Predictive Control (MPC) problem through enumerating the model jump scenarios. Finally, to meet the real-time performance of the WECS, the method of off-line calculating and online calling the controller is adopted to improve the operation speed of SMPC. Simulation results show that the proposed SMPC method has good control performance.