网络首发:2026-06-04,
纸质出版:2026
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姚琦, 黄耀湘, 寇燕妮, 等. 基于WOA-AMPC双层框架的风电场增效降损控制研究[J]. 太阳能学报, 2026,47(5):237-246.
姚琦, 黄耀湘, 寇燕妮, et al. 基于WOA-AMPC双层框架的风电场增效降损控制研究[J]. 2026, 47(5): 237-246.
姚琦, 黄耀湘, 寇燕妮, 等. 基于WOA-AMPC双层框架的风电场增效降损控制研究[J]. 太阳能学报, 2026,47(5):237-246. DOI: 10.19912/j.0254-0096.tynxb.2024-2310.
姚琦, 黄耀湘, 寇燕妮, et al. 基于WOA-AMPC双层框架的风电场增效降损控制研究[J]. 2026, 47(5): 237-246. DOI: 10.19912/j.0254-0096.tynxb.2024-2310.
尾流效应会导致风电场出现功率损失
但现有主动尾流控制存在造成风电机组额外机械载荷的风险。针对这一问题
该文结合鲸鱼优化算法与自适应模型预测控制
提出场站-机组协同的主动尾流和机组载荷双层控制方案
场站层通过主动尾流控制改变尾流方向
机组层面则在指定偏航角的前提下
利用桨距角和转矩的二自由度控制
完成功率提升和载荷抑制。考虑到机组偏航状态下二自由度控制的复杂性
设计模糊推理机制
根据机组运行模态和环境变化实现模型预测控制的自适应调参。仿真结果表明
对比传统单机最大功率点跟踪控制方案
所提方案在较大风速范围内具有提升风电场出力水平5.03%~7.87%
同时实现站内机组塔架和主轴的载荷抑制。
Wake effects can lead to power loss in wind farms
but existing active wake control has the risk of causing additional mechanical loads on wind turbines. To solve this problem
this paper combines the whale optimization algorithm and adaptive model predictive control
and proposes a two-layer control scheme of active wake and load of the unit in which the wind-farm level changes the wake direction through active wake control
and the unit level uses the two-degree-of-freedom control of pitch angle and torque under the premise of designated yaw angle to complete power increase and load suppression. Considering the complexity of two-degree-of-freedom control under turbine yaw conditions
a fuzzy inference mechanism is designed to realize the adaptive parameter adjustment of model predictive control according to the operating modes and environmental changes. The simulation results show that compared with the traditional single-turbine maximum power point tracking control scheme
the proposed scheme can increase the output level of the wind farm by 5.03%-7.87% in a large wind speed range
and realize load suppression of the unit tower and main shaft witnin the wind farm.
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