深度学习在电网安全管理系统中的风险识别算法研究  

Research on Risk Identification Algorithm in Power Grid Safety Management System Based on Deep Learning

作　　者：董捷 吴扬 DONG Jie;WU Yang(State Grid Ningxia Electric Power Co.,Ltd.Yinchuan Power Supply Company Jinfeng District Power Supply Company,Yinchuan Ningxia 750001,China)

机构地区：[1]国网宁夏电力有限公司银川供电公司金凤区供电公司,宁夏银川750001

出　　处：《信息与电脑》2024年第8期170-172,共3页Information & Computer

摘　　要：随着电力系统规模和智能化水平的扩大,电网安全管理面临复杂挑战。传统方法存在盲区和误差,难以准确评估风险。本研究探讨利用深度学习技术提高风险识别,构建新算法框架,支持安全管理演化,提升风险评估精准性。深度学习消除了监测盲区,减少了误差,帮助管理者应对系统复杂性。结合历史数据和实时监测信息,深度学习还可以用来建立强大风险识别模型。通过优化算法,电网系统风险的实时监测和预警可被实现,为安全管理提供可靠支持。With the expansion of the scale and intelligence level of the power system,power grid safety management is facing complex challenges.Traditional methods have blind spots and errors,making it difficult to accurately assess risks.This study explores the use of deep learning technology to improve risk identification,by constructing a new algorithm framework,to support the evolution of security management,and enhance the accuracy of risk assessment.Deep learning eliminates monitoring blind spots,reduces errors,and helps managers cope with system complexity.Deep learning can also be used to establish a powerful risk identification model by combining historical data and real-time monitoring information.By optimizing algorithms,real-time monitoring and early warning of power grid system risks can be achieved,providing reliable support for safety management.

关 键 词：电网安全管理 风险识别 深度学习技术 算法框架 实时监测 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]