Health-aware Model Predictive Control of Wind Turbines using Stifness Degradation Approach

Wind turbine blades are under significant gravitational, inertial, and aero-dynamic loads, which cause their fatigue and degradation during the wind turbine operational life. The present work proposes a Model Predictive Control scheme that integrates remaining useful life predictions of the blade based on a stiffness degradation model embedded in a prognostics algorithm. The flapwise blade root bending loads are used as inputs to the damage model which describes the propagation of damage from a microscopical scale manifesting in a macroscopical scale as stiffness loss. The proposed control scheme integrates prognostics information in the MPC formulation in order to optimize the trade-off that exists between the conflictive objectives of producing power and extend the remaining useful life of the blades. The proposed control scheme has been tested using the sensor information from the well known high fidelity wind turbine simulator FAST (Fatigue, Aerodynamics, Structures and Turbulence). Copyright (C) 2020 The Authors.