Scenario-based stochastic model predictive control for wind energy conversion system

Abstract

This paper develops an approach for wind energy conversion system (WECS) control based on stochastic model predictive control (SMPC). The structure combines the Markov chain that illustrates the WECS behavior, a stochastic optimization method based on scenario, and quadratic programming. By using quadratic programming, SMPC can generally handle larger dimension of state model than stochastic dynamic programming for changes of WECS behavior. The simulation results demonstrate the effectiveness of the optimal control of WECS by scenario-based stochastic model predictive control algorithm.