基于模糊K-均值算法的双馈风电场故障特性等值建模

高泽; 刘明洋; 李程昊; 王义; 田春笋

doi:10.19912/j.0254-0096.tynxb.2024-2297

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (5) : 227-236. DOI: 10.19912/j.0254-0096.tynxb.2024-2297

基于模糊K-均值算法的双馈风电场故障特性等值建模

高泽¹, 刘明洋¹, 李程昊¹, 王义², 田春笋¹

作者信息 +

EQUIVALENT MODELING OF FAULT CHARACTERISTICS OF DOUBLY-FED WIND FARM BASED ON FUZZY K-MEANS ALGORITHM

Gao Ze¹, Liu Mingyang¹, Li Chenghao¹, Wang Yi², Tian Chunsun¹

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文章历史 +

摘要

为提高风电场等值建模精度,提出一种基于模糊K-均值算法的双馈风电场故障特性等值建模方法。首先,依据故障期间双馈感应式风力发电机的动态特性,选择机端电压扰动特性指标、风速和转子角速度作为风电场机组聚类指标;其次,采用蜜獾算法和模糊熵优化K-均值算法的初始聚类中心选择过程,提升聚类精度,并对机组进行分群;之后,将各群内机组等值为单台机组并计算等值参数。最后,以河南省某实际双馈风电场站为算例进行测试分析验证,测试结果表明所提等值建模方法能够更加准确地反映风电场故障特性。

Abstract

In order to improve the accuracy of wind farm equivalent modeling, this paper presents a method of fault characteristic equivalent modeling based on fuzzy K-means algorithm for doubly-fed wind farm. First, terminal voltage disturbance characteristic index, wind speed, and rotor angular velocity are selected as clustering indicators for wind turbine grouping. Secondly, honey badger algorithm and fuzzy entropy are used to optimize the initial clustering center selection process of K-means algorithm, which improves the accuracy of clustering and groups the units; then, each unit in the cluster is equivalent to one unit and the equivalent parameters are calculated. Finally, a practical doubly fed wind farm in Henan Province is taken as an example to test and analyze, and the test results show that the proposed equivalent modeling method can reflect the fault characteristics of wind farm more accurately.

导出引用

高泽, 刘明洋, 李程昊, 王义, 田春笋. 基于模糊K-均值算法的双馈风电场故障特性等值建模[J]. 太阳能学报. 2026, 47(5): 227-236 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2297

Gao Ze, Liu Mingyang, Li Chenghao, Wang Yi, Tian Chunsun. EQUIVALENT MODELING OF FAULT CHARACTERISTICS OF DOUBLY-FED WIND FARM BASED ON FUZZY K-MEANS ALGORITHM[J]. Acta Energiae Solaris Sinica. 2026, 47(5): 227-236 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2297

中图分类号： TM614

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