Optimization Modeling of Active Power Dispatch in Wind Farms Considering Wind Turbine Fatigue Damage

With the rapid advancement of wind power technology in China, large-scale wind turbines are widely deployed, making optimization of wind farm scheduling essential for improving power generation efficiency and reducing maintenance costs. This study proposes an active power dispatch optimization model that considers wind turbine fatigue damage. First, a low-complexity fatigue damage model is established using wind turbine load data, predicting key mechanical loads such as main shaft torque and tower thrust based on wind speed, active power, and system dynamics. Then, a real-time power dispatch optimization model is developed, integrating power system scheduling instructions and employing a gradient descent algorithm to optimize power allocation while minimizing overall fatigue damage. To enhance robustness, a Kalman filtering algorithm is introduced. Finally, real wind farm data is used for validation. The results demonstrate that the proposed model effectively meets external grid scheduling requirements, optimizes power distribution, and significantly reduces turbine fatigue damage and maintenance costs. Compared to conventional average power allocation methods, this strategy achieves a more balanced fatigue load distribution, prolonging turbine lifespan and enhancing operational stability. This research provides a feasible solution for wind farm power optimization, contributing to improved economic performance and system reliability.