中圖分類號：TP391.9文獻標識碼：ADOI:10.19358/j.issn.2097-1788.2025.02.002
引用格式：邱情芳，曹學銘，王丹丹，等. 基于神經(jīng)網(wǎng)絡的大型無人值守風電場網(wǎng)絡安全監(jiān)控技術研究［J］.網(wǎng)絡安全與數(shù)據(jù)治理，2025，44（2）：10-16，31.

Research on network security monitoring technology for large unmanned wind farm based on neural network

Abstract： Large-scale unmanned wind farm is an important component of clean energy,and its network security not only relates to the stable operation of wind farms,but also directly affects the security of the entire power system.Therefore,this study aims to explore the network security monitoring technology for large-scale unmanned wind farms based on neural networks,in order to improve the network security protection capability of wind farms. This study first analyzed the network security threats of large unmanned wind farms,including external attacks,internal leaks,equipment failures etc. In response to these threats,this study designed a neural network-based network security monitoring model that can monitor key information such as network traffic and equipment status of wind farms in real time,and identify and warn of abnormal behavior through deep learning algorithms. In order to verify the effectiveness of the model,experiments were conducted in a simulated wind farm environment. The results showed that the model can accurately identify various network security threats and issue early warnings，providing strong support for the network security protection of wind farms.

Key words : wind farm; network security; security monitoring; neural network