Abstract: For the significant fatigue damage to critical components such as the main shaft and tower of wind turbines in wind power generation, as well as the issue where the traditional active power average allocation strategy in wind farms leads to certain turbines operating under high loads for extended periods, this paper proposes an active power optimization allocation method based on fatigue damage characteristics of wind power. First, to account for the influence of the geographical environment on turbine fatigue damage, a novel calculation model is established for main shaft torque and tower thrust based on environmental temperature, wind speed, and altitude by combining the ideal gas equation of state with force analysis of air units. Second, by improving the three-point rain-flow counting method, the effective cycle count, load amplitude, and mean load can be calculated more accurately. On this basis, a nonlinear time-varying fatigue damage model considering wind power generation characteristics is further constructed. Finally, the FATA optimization algorithm is employed to solve the wind farm active power optimization allocation problem, aiming to minimize the fatigue damage level of wind turbines. Simulation results from actual case studies demonstrate that, compared to the traditional average allocation strategy, this method significantly reduces turbine fatigue damage while ensuring accurate tracking of grid dispatch commands by the wind farm’s delivered power. This provides valuable theoretical and applied references for the safe and economic operation of wind farms.

Key words: wind farm, wind power generation characteristics, real-time rain-flow counting method, nonlinear cumulative fatigue damage, fata morgana algorithm(FATA)