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
王德星1
作者信息
- 1. 国电投南通新能源公司,江苏 南通 226400
- 折叠
摘要
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.
Abstract
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.
关键词
海上风电/卷积神经网络/继电保护/状态监测Key words
offshore vind power/convolutional neural networks/relay protection/state monitoring引用本文复制引用
出版年
2024
NETL
NSTL
万方数据