首页|基于深度学习的800kV直流输电线路运行检修技术

基于深度学习的800kV直流输电线路运行检修技术

扫码查看
随着特高压直流输电技术的快速发展,800 kV直流输电线路的运行检修面临巨大挑战.因此,文章提出一种基于深度学习的800 kV直流输电线路运行检修技术方案.通过多维度、高精度的数据采集,获取线路状态信息.在此基础上,构建融合卷积神经网络(Convolutional Neural Network,CNN)与长短期记忆(Long Short-Term Memory,LSTM)网络的混合深度学习模型,实现高效、准确的故障诊断.结合智能化检修规划策略,优化检修资源配置和任务调度.本研究为特高压直流输电线路的智能化运维提供了新的技术路径.
Research on Technologies for Operation and Maintenance of 800 kV Direct Current Transmission Lines Based on Deep Learning
With the rapid development of ultra-high voltage direct current transmission technology,the operation and maintenance of 800 kV direct current transmission lines are facing great challenges.Therefore,this paper proposes a technical scheme for operation and maintenance of 800 kV direct current transmission lines based on deep learning.Through multi-dimensional and high-precision data acquisition,the line state information is obtained.On this basis,a hybrid deep learning model combining Convolutional Neural Network(CNN)and Long Short-Term Memory(LSTM)network is constructed to realize efficient and accurate fault diagnosis.Combined with intelligent maintenance planning strategy,optimize maintenance resource allocation and task scheduling.This study provides a new technical path for intelligent operation and maintenance of ultra-high voltage direct current transmission lines.

deep learning800 kV direct current power transmissionoperation and maintenance

李永强、李巍、谢晋元、王辉

展开 >

国网甘肃省电力公司超高压电公司,甘肃兰州 730050

深度学习 800kV直流输电 运行检修

2024

通信电源技术
武汉普天通信设备集团有限公司

通信电源技术

影响因子:0.389
ISSN:1009-3664
年,卷(期):2024.41(21)