智能电网环境下配网调度系统及关键技术研究  

Research on Distribution Network Scheduling System and Key Technologies in Smart Grid Environment

作　　者：郭剑黎 彭磊 郭祥富 许国伟 武柯 GUO Jianli;PENG Lei;GUO Xiangfu;XU Guowei;WU Ke(State Grid Henan Electric Power Company,Zhengzhou 450000,China;Henan Jiuyu Tenglong Information Engineering Co.,Ltd.,Zhengzhou 450000,China)

机构地区：[1]国网河南省电力公司,河南郑州450000 [2]河南九域腾龙信息工程有限公司,河南郑州450000

出　　处：《微型电脑应用》2023年第12期179-182,190,共5页Microcomputer Applications

摘　　要：当前配网调度系统存在的技术弊端,无法实现配网调度的智能化、信息化,为此通过分布式网络拓扑架构实现配网数据信息的传递、分析与综合管理,使用微电流计算法(CES)的综合能源系统(IES)实现不同数据信息分层与调度,大大提高了能源综合分配能力。该方法中应用深度学习模型(GDL)实现配网调度故障诊断,实现配网调度系统内深层数据挖掘与分析。实验表明,该研究配网调度完成所需时间最少为1 s,准确性可达97%。The current distribution network scheduling system has some technical shortcomings.It is impossible to realize the intelligence and informatization of distribution network scheduling.This research uses micro-current calculation method to realize the transmission,analysis and comprehensive management of distribution network data information through the distributed network topology architecture.The integrated energy system(IES)of cranial electrotherapy stimulation(CES)realizes the stratification and scheduling of different data information,which greatly improves the comprehensive energy distribution capability.This method is implemented by the deep learning model.The fault diagnosis of distribution network dispatching realizes deep data mining and analysis in the distribution network dispatching system.Experiments show that the time required to complete the distribution network scheduling in this study is at least 1 s,and the accuracy can reach 97%.

关 键 词：配网调度 智能电网 GDL 自动化 深度学习 

分 类 号：TM734[电气工程—电力系统及自动化]