摘要
针对水电站电力监控系统面临的复杂安全威胁,设计了基于态势感知的监控系统。该系统通过分布式数据采集、集中智能分析与协同响应机制,融合深度学习与动态博弈理论,实现对多源数据的实时感知与威胁精准识别。通过在高保真仿真环境下进行验证,实验结果表明,该系统在高并发情况下的事件处理吞吐量达到5382条/s,响应延迟控制在147 ms,检测准确率分别为95.1%、94.6%、96%,有效提升了安全防护能力。在复杂攻防场景中,系统成功拦截攻击比例达到93.7%,显示出优异的实时防护效果。
A monitoring system based on situation awareness is designed to address the complex security threats faced by power monitoring systems in hydropower stations.In this system,real-time perception of multi-source data and precise identification of threats are achieved through the integration of distributed data collection,centralized intelligent analysis,and collaborative response mechanisms,along with the application of deep learning and dynamic game theory.Verification is carried out in a high-fidelity simulation environment,and the experimental results demonstrate that the event processing throughput of the system reaches 5382 items per second under high-concurrency conditions,with the response delay being controlled at 147 ms.The detection accuracy rates are reported as 95.1%,94.6%,and 96%,respectively,which effectively enhances the security protection capability.In complex attack-defense scenarios,93.7%of attacks are successfully intercepted by the system,indicating its excellent real-time protection performance.
作者
刘航通
王帅帅
朱咏敏
LIU Hangtong;WANG Shuaishuai;ZHU Yongmin(Xinanjiang Hydropower Plant of State Grid Xinyuan Group Co.,Ltd.,Hangzhou,Zhejiang 311600,China)
出处
《自动化应用》
2025年第23期179-181,184,共4页
Automation Application
关键词
水电站
电力监控
态势感知
协同响应机制
高并发情况
安全防护能力
hydropower station
power monitoring
situation awareness
collaborative response mechanisms
highconcurrency conditions
security protection capability
