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作 者:潘宁 PAN Ning(Jiangsu Offshore Longyuan New Energy Co.,Ltd.,Nantong 226000,China)
机构地区:[1]江苏海上龙源新能源有限公司,江苏南通226000
出 处:《通信电源技术》2025年第2期64-66,共3页Telecom Power Technology
摘 要:随着新能源大规模接入电网,电力通信网络面临新的可靠性挑战。提出一种基于新能源接入的电力通信网络可靠性评估技术。该技术通过多源异构数据采集与预处理、深度学习特征提取与选择、长短期记忆-图卷积网络(Long Short Term Memory-Graph Convolutional Network,LSTM-GCN)混合模型设计等关键技术,精确评估新能源环境下电力通信网络可靠性。实验结果表明,该技术在网络可靠度、平均故障间隔时间、故障恢复时间及业务可用度等方面的表现均优于基于可靠性框图的技术和基于贝叶斯网络的技术。With the large-scale integration of new energy into the power grid,the power communication network is facing new reliability challenges.The article proposes a reliability evaluation technology for power communication networks based on new energy access.This technology achieves accurate evaluation of the reliability of power communication networks in the new energy environment through key technologies such as multi-source heterogeneous data acquisition and preprocessing,deep learning feature extraction and selection,and Long Short Term MemoryGraph Convolutional Network(LSTM-GCN)hybrid model design.The experimental results show that this technology outperforms existing methods in core indicators such as network availability,fault recovery time,and end-to-end latency,significantly improving evaluation accuracy and adaptability.
分 类 号:TM7[电气工程—电力系统及自动化]
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