基于深度学习的安顺电网调控OCS系统告警优化方法

The Warning Optimality Method of Anshun Grid Regulation and Control OCS System Based on Depth Study

为提升安顺电网调控OCS系统告警效果,研究提出了一种基于深度学习的安顺电网调控OCS系统告警优化方法。该方法先基于深度学习理论完成电网调控系统告警架构优化设计,然后基于LSTM模型完成电网调控OCS系统告警状态预测,最后以预测结果为基础,对其告警信号进行分类,完成电网调控OCS系统告警行为优化设计。实验结果表明,应用所提方法进行安顺电网调控OCS系统告警优化后,其告警准更高、响应时间更短,应用效果更好。

In order to improve warning effect of Anshun grid regulation and control OCS system,in the study,put forward a warning optimatlity method of Anshun grid regulation and control OCS system based on depth study.First,the method completes warning structure optimality design of the grid regulation and control system based on depth study theory,then completes warning state forecast of the grid regulation and control OCS system based on LSTM model.Finally,on the basis of forecast results,classify its warning signals to complete the warning behaviollr optimality design of the grid regulation and control OCS system.The results show that after adopting An shun grid regulation and control OCS system waring optimality proposed method,its warning is more accurate,response time is shorter and application effect is better.