Optimal scheduling of active power in wind farms considering fatigue damage suppression

Wind turbines operate under complex and variable wind conditions, leading to frequent load fluctuations and cumulative fatigue damage. To investigate fatigue-aware wind farm operation, this paper proposes an active power optimization scheduling model that incorporates fatigue suppression. A fatigue evaluation framework based on the three-point rain-flow counting method and Miner’s linear damage rule is developed to quantify the fatigue levels of the main shaft and tower. Stress and torque estimation models are constructed using operational data such as wind speed and rotor speed, with multiple linear regression applied to predict fatigue loads. A constrained dispatch model is then formulated to minimize a squared-load surrogate while meeting the prescribed total power, with the non-dominated sorting genetic algorithm II (NSGA-II) retained as the original search framework. Numerical results involving 100 wind turbines report reduced aggregate load-based indices under the original calculation. These indices do not establish physical fatigue-life extension; component calibration and dynamic validation remain necessary.