Model Predictive Control for Wind Turbine Load Reduction under Wake Meandering of Upstream Wind Turbines

In wind farm operation, the performance and loads of downstream turbines are heavily influenced by the wake of the upstream turbines. Furthermore, the actual wake is more challenging due to the dynamic phenomenon of wake meandering, i.e. the turbine wake often demonstrates dynamic shift over time. To deal with the time-varying characteristics of wake meandering, the dual-mode linear quadratic model predictive control (LQMPC) scheme is applied to the individual pitch control (IPC) based load reduction. The coherence function along the lateral direction in the spectral method is used to generate the stochastic wind profile including wake meandering at upstream turbine, and a simplified wake meandering model is developed to emulate the trajectory of the wake center at downstream turbine. The Larsen wake model and Gaussian distribution of wake deficit are applied for composing wind profiles across the rotor of downstream turbines. State-space models are derived via the Blade Element Momentum (BEM) theory. A set of MPC controllers are designed based on different linearized state-space models, and are applied in a switching manner. Simulation results show the reduction in the blade-root flapwise moment and the rotor speed variation.