湖南电力 ›› 2026, Vol. 46 ›› Issue (4): 20-25.doi: 10.3969/j.issn.1008-0198.2026.04.004

• 源网协调与能源转换利用 • 上一篇    下一篇

基于风电疲劳损伤特性的有功功率优化分配

屈俊辉, 籍宏震, 窦笛, 廖小雨   

  1. 长沙理工大学电网防灾减灾全国重点实验室,湖南 长沙 410114
  • 收稿日期:2026-02-09 修回日期:2026-03-24 出版日期:2026-08-25 发布日期:2026-09-11
  • 作者简介:屈俊辉(2001),硕士研究生,主要研究方向为风电机组疲劳损失、风电功率预测。
  • 基金资助:
    湖南省研究生科研创新项目(CX20240077)

Optimization of Active Power Allocation Based on Fatigue Damage Characteristics of Wind Power

QU Junhui, JI Hongzhen, DOU Di, LIAO Xiaoyu   

  1. State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410114, China
  • Received:2026-02-09 Revised:2026-03-24 Online:2026-08-25 Published:2026-09-11

摘要: 风电场传统有功功率平均分配策略导致部分机组长期高负荷运行,风电机组主轴和塔架等关键部件在发电中疲劳损伤显著。针对此问题,提出一种基于风电疲劳损伤特性的有功功率优化分配方法。首先,考虑地理环境对风电机组疲劳损伤的影响,通过理想气体状态方程,结合空气单元的受力分析,建立基于环境温度、风速和海拔的主轴扭矩与塔架推力计算模型。其次,通过改进三点雨流计数法,精确计算载荷的有效循环次数、载荷幅值与均值,在此基础上,构建考虑风力发电特性的非线性时变疲劳损伤模型。最后,通过海市蜃楼优化算法实现以风电机组疲劳损伤程度最小为目标的风电场有功功率优化分配。实际案例仿真表明,与传统平均分配策略相比,该方法能显著降低风电机组的疲劳损伤,同时确保风电场输送功率精确跟踪电网调度指令;在满足电网功率调度的前提下,降低场站所有风电机组总体疲劳损伤程度,为风电场的安全、经济运行提供有价值的理论与应用参考。

关键词: 风电场, 风力发电特性, 实时雨流计数法, 非线性累积疲劳损伤, 海市蜃楼优化算法(FATA)

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)

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