首页|基于CNN的海上风电交流送出线路继电保护状态监测技术研究

基于CNN的海上风电交流送出线路继电保护状态监测技术研究

Research on the State Monitoring Technology of Relay Protection for Offshore Wind Power AC Transmission Lines Based on CNN

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为了提高海上风电场的可靠性,深入探讨了基于卷积神经网络(CNN)的海上风电交流送出线路继电保护状态监测技术.该技术通过实时采集继电保护设备的多维度运行数据,构建多视图数据集,并设计了一种融合多视图特征的CNN模型,用于评估继电保护设备的健康状态.与传统单视图的方法相比,多视图CNN能更全面地挖掘设备运行状态的内在关联,提高状态评估的准确性.
In order to enhance the reliability of offshore wind farms,this paper deeply explores the state monitoring tech-nology of relay protection for offshore wind power AC transmission lines based on Convolutional Neural Networks(CNN).The technology collects multidimensional operational data of relay protection equipment in real time,constructs a multi-view dataset,and designs a CNN model that integrates multi-view features to assess the health status of relay protection equipment.Compared with traditional single-view methods,multi-view CNN can more comprehensively explore the intrin-sic correlations of equipment operation status,improving the accuracy of status assessment.

offshore vind powerconvolutional neural networksrelay protectionstate monitoring

王德星

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国电投南通新能源公司,江苏 南通 226400

海上风电 卷积神经网络 继电保护 状态监测

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(22)