基于深度学习的电力调度数据自动备份系统设计  

Design of power dispatching data automatic backup system based on deep learning

作　　者：赵英宝[1] 黄丽敏[1] 刘慧贤[1] ZHAO Yingbao;HUANG Limin;LIU Huixian(Hebei University of Science and Technology,Shijiazhuang 050018,China)

机构地区：[1]河北科技大学,河北石家庄050018

出　　处：《现代电子技术》2020年第20期42-45,49,共5页Modern Electronics Technique

基　　金：国家自然科学基金项目(51507048)。

摘　　要：针对传统电力调度数据自动备份系统缺少对电力数据的调度处理,导致其方法存在稳定性较差等问题,提出基于深度学习的电力调度数据自动备份系统。电力系统调度模块利用深度学习网络,构建不良数据辨识模型,排除电力系统中的不良数据,并生成电力调度数据;电力调度数据备份模块采用在线数据备份模式,并结合深度学习理论,对电力调度数据进行统一备份、恢复和备份介质管理。实验结果表明,文中设计系统能够满足电力调度数据备份的要求,且系统稳定性较强,可以证明该系统的实际应用效果更好。In allusion to the problem that the traditional automatic backup system of power dispatching data lacks the dispatching processing of power data,which leads to the poor stability of the system,a deep learning based automatic backup system of power dispatching data is proposed.Based on deep learning network,the power system dispatching module is used to construct the identification model for bad data,eliminate the bad data in the power system,and generate the power dispatching data.The power dispatching data backup module is used to perform the unified backup,recovery and backup media management of the power dispatching data by means of the online data backup mode and in combination with the deep learning theory.The experimental results show that the system designed in this paper can meet the requirements of power scheduling data backup,and has strong stability,which can prove that the system is more effective in practical application.

关 键 词：电力调度数据 自动备份系统 系统设计 深度学习 辨识模型建立 数据处理 

分 类 号：TN919-34[电子电信—通信与信息系统] TP311.52[电子电信—信息与通信工程]