海上风电机组关键温度测点虚拟感知及应用方法

程逸; 张杨宇; 胡阳; 胡耀宗; 刘冰冰; 刘吉臻

doi:10.19912/j.0254-0096.tynxb.2024-1115

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太阳能学报 ›› 2025, Vol. 46 ›› Issue (10) : 735-745. DOI: 10.19912/j.0254-0096.tynxb.2024-1115

海上风电机组关键温度测点虚拟感知及应用方法

程逸¹, 张杨宇¹, 胡阳¹, 胡耀宗¹, 刘冰冰², 刘吉臻¹

作者信息 +

VIRTUAL PERCEPTION AND APPLICATION METHOD FOR KEY TEMPERATURE MEASUREMENT POINTS OF OFFSHORE WIND TURBINES

Cheng Yi¹, Zhang Yangyu¹, Hu Yang¹, Hu Yaozong¹, Liu Bingbing², Liu Jizhen¹

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文章历史 +

摘要

针对东南沿海高温高湿环境下海上风电机组易发生超温故障的运行难题,提出一种有限差分域-深度神经网络（FDD-DNN）的关键温度测点虚拟感知及应用方法。首先,提出机理分析与孤立森林算法融合的高维异常运行数据识别方法、高维相似工况联合的缺失数据填补方法;然后,定义可表征机组运行工况和时滞特性的有限差分回归向量,引入软间隔支持向量机（SSVM）划分差分动态运行域;在此基础上提出基于深度神经网络（DNN）的分域时序动态建模方法,完成全工况运行特性下的关键温度测点精细化表征及虚拟感知。最后,提出虚拟感知模型部署及应用的工程方法。以海上风电机组的主轴温度为例,结果表明：所提出的方法各项评价指标均有提升。

Abstract

To address the operational challenge of offshore wind turbines in the high-temperature and high-humidity environment of the southeastern coast, which are prone to overheating faults, a key temperature measurement point virtual perception and application method based on finite difference domain-deep neural networks （FDD-DNN） is proposed. Firstly, a high-dimensional abnormal operational data identification method integrating mechanism analysis and Isolation Forest algorithm, as well as a high-dimensional similar condition-based missing data imputation method, is proposed. Then, a finite difference regression vector that can characterize the operational conditions and time-delay characteristics of the wind turbine is defined, and a soft margin support vector machine （SSVM） is introduced to partition the differential dynamic operational domain. On this basis, a domain-based temporal dynamic modeling method based on DNN is proposed to achieve refined characterization and virtual perception of key temperature measurement points under full operational conditions. Finally, an engineering method for the deployment and application of the virtual perception model is proposed. Taking the main shaft temperature of offshore wind turbines as an example, the results show that the proposed method improves all evaluation metrics.

导出引用

程逸, 张杨宇, 胡阳, 胡耀宗, 刘冰冰, 刘吉臻. 海上风电机组关键温度测点虚拟感知及应用方法[J]. 太阳能学报. 2025, 46(10): 735-745 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1115

Cheng Yi, Zhang Yangyu, Hu Yang, Hu Yaozong, Liu Bingbing, Liu Jizhen. VIRTUAL PERCEPTION AND APPLICATION METHOD FOR KEY TEMPERATURE MEASUREMENT POINTS OF OFFSHORE WIND TURBINES[J]. Acta Energiae Solaris Sinica. 2025, 46(10): 735-745 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1115

中图分类号： TM614

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