永磁同步风电机组发电机定子温度建模方法

杨明岱, 王宪, 赵前程, 胡芳, 阳雪兵

太阳能学报 ›› 2022, Vol. 43 ›› Issue (5) : 319-326.

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (5) : 319-326. DOI: 10.19912/j.0254-0096.tynxb.2020-0891

永磁同步风电机组发电机定子温度建模方法

  • 杨明岱1, 王宪1, 赵前程1, 胡芳2, 阳雪兵2
作者信息 +

MODELING METHOD OF STATOR TEMPERATURE OF PMSG WIND TURBINE

  • Yang Mingdai1, Wang Xian1, Zhao Qiancheng1, Hu Fang2, Yang Xuebing2
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文章历史 +

摘要

针对山地风电场大型永磁同步风电机组发电机定子温度的变化特点及传热过程进行分析,提出一种基于风电机组SCADA数据的发电机定子温度建模方法。首先,分析风电机组在实际运行过程中定子温度的变化情况;然后,根据永磁同步发电机内部的传热过程,对发电机定子温度建模;最后,采用风电机组正常运行时的SCADA数据求解模型参数。实例分析表明,风电机组状态正常时,定子温度估计的平均误差绝对值为0.59 ℃,模型精度较高;风电机组状态异常时,模型温度估计的平均误差绝对值为5.17 ℃,精度显著降低。

Abstract

By analyzing the temperature change characteristics and heat transfer process of the generator stator of large permanent magnet synchronous generator (PMSG) in mountain wind farm, a wind turbine SCADA data-based generator stator temperature modeling method was proposed in this paper. Firstly, the change of stator temperature in the operating process of wind turbine was analyzed and then the generator stator temperature was modeled according to the heat transfer process in PMSG; Finally, the model parameters were solved by using SCADA data of wind turbine in normal operation. According to the instance analysis results, the average error absolute of temperature estimation of the model is 0.59 ℃ and the model is highly accurate when the wind turbine is in normal state; when the wind turbine state is abnormal, the average error absolute of the model temperature estimation is 5.17 ℃, and the accuracy is significantly reduced. The model can be used for wind turbine state assessment.

关键词

风力发电 / 风电机组 / 定子 / 永磁同步发电机 / 温度数据分析 / 状态监测

Key words

wind power / wind turbines / stators / PMSG / temperature data analysis / status report

引用本文

导出引用
杨明岱, 王宪, 赵前程, 胡芳, 阳雪兵. 永磁同步风电机组发电机定子温度建模方法[J]. 太阳能学报. 2022, 43(5): 319-326 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0891
Yang Mingdai, Wang Xian, Zhao Qiancheng, Hu Fang, Yang Xuebing. MODELING METHOD OF STATOR TEMPERATURE OF PMSG WIND TURBINE[J]. Acta Energiae Solaris Sinica. 2022, 43(5): 319-326 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0891
中图分类号: TH17    TK83   

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基金

国家自然科学基金(51875199); 国家重点研发计划(2016YFF0203400); 湖南省战略性新兴产业科技攻关与重大成果转化专项(2018GK4024); 湖南省重点研发计划(2018GK2073)

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