高效风能捕获的高空风电优化运行控制策略

付炳喆; 王玮; 罗必雄; 任宗栋; 李沂洹; 杨卧龙

doi:doi:10.19912/j.0254-0096.tynxb.2024-0965

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高效风能捕获的高空风电优化运行控制策略

更新时间：2025-12-10

- 高效风能捕获的高空风电优化运行控制策略
- Issue 11, Pages: 581-589(2025)
- 作者机构：
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- DOI：doi:10.19912/j.0254-0096.tynxb.2024-0965
  CLC： M614
- Published Online：04 December 2025，
  
  Published：04 December 2025
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付炳喆, 王玮, 罗必雄, et al. 高效风能捕获的高空风电优化运行控制策略[J]. 2025, (11): 581-589.
DOI：

付炳喆, 王玮, 罗必雄, et al. 高效风能捕获的高空风电优化运行控制策略[J]. 2025, (11): 581-589. DOI： doi:10.19912/j.0254-0096.tynxb.2024-0965.

摘要

为实现适应风切变动态变化的高空风力发电系统（AWEs）运行优化控制

达成高效风能捕获

提出一种基于混合高斯过程（MGP）的自适应模型预测控制（MPC）策略。首先

对AWEs运行的关键因素风切变定量分析

使用混合高斯过程对风切变剖面的重要统计特征建模

为高度优化控制提供先验风速信息;然后

建立融合遗传算法的自适应MPC策略以实现运行最优高度和能量损耗之间的平衡

在保证AWE系统运行在理想高度的同时减少控制所消耗的能量

提升AWEs的净发电量;最后

基于中国某高空风能发电示范工程的真实风切变数据验证所提出优化运行控制策略。结果表明

该策略可有效提升AWEs净发电量

较传统固定塔架结构风电机组平均提升18.9%

较极值搜索策略提升9.6%。

Abstract

To achieve the optimization control of airborne wind energy systems （AWEs） that adapt to the dynamic changes of wind shear

and to accomplish efficient wind energy capture

a model predictive control （MPC） strategy based on mixed Gaussian process（MGP） is proposed. Initially

a quantitative analysis of the key factor of AWEs operation

wind shear

is conducted. MGP is utilized to model the significant statistical characteristics of the wind shear profile

providing prior wind speed information for height-optimized control. Subsequently

an adaptive MPC strategy integrated with a genetic algorithm is established to balance the optimal operation height and energy dissipation

ensuring that AWEs operates at the ideal height while reducing the energy consumed for control

thereby enhancing the net power generation of AWEs. Finally

the proposed optimization control strategy is validated based on the real wind shear data from a high-altitude wind energy generation demonstration project in China. The results indicate that the strategy can effectively increase the net power generation of AWEs

with an average increase of 18.9% compared to traditional fixed tower structures and 9.6% compared to the extremum seeking strategy.

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Keywords

references

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