基于泛在互联的电网运行数据管控系统设计  

Design of power grid operation data management and control system based on ubiquitous interconnection

作　　者：叶清 肖飞 李林锐 黄磊 黄冰飞 YE Qing;XIAO Fei;LI Linrui;HUANG Lei;HUANG Bingfei(Qingpu Power Supply Company of SMEPC,Shanghai 201799,China)

机构地区：[1]国网上海市电力公司青浦供电公司,上海201799

出　　处：《电子设计工程》2020年第20期153-157,共5页Electronic Design Engineering

基　　金：青浦供电公司2019年度群众性创新科技项目(“举手制”试点实施项目)(52093419002F)。

摘　　要：针对数据采集分析技术在电网风险评估领域的应用问题。文中从智能感知层、大数据平台和业务应用层这3个层面出发,设计架构了基于泛在物联与数据挖掘的电网运行数据采集分析系统,并进一步提出了基于电网运行数据的人工神经网络(ANN)风险评估方法。文中所提方法包括生成训练样本并用其训练ANN模型,以及利用训练好的ANN模型进行实时风险评估两个过程。通过对某地电网进行仿真验算的结果表明,该ANN风险评估方法的准确率可达93%以上,平均耗时小于1 s,从而能够快速、准确地评估电网风险等级。Aiming at the application of data acquisition and analysis technology in the field of power grid risk assessment.In this paper,from the three levels of intelligent sensing layer,big data platform and business application layer,a power grid operation data acquisition and analysis system based on ubiquitous IOT and data mining is designed,and an artificial neural network(ANN)risk assessment method based on power grid operation data is further proposed.The method proposed in this paper includes two processes:generating training samples,training ANN model and real⁃time risk assessment.The simulation results of a certain power grid show that the accuracy of the ANN risk assessment method is more than 93%,and the average time is less than 1 s,which can quickly and accurately assess the risk level of the power grid.

关 键 词：数据采集分析 运行数据 风险评估 人工神经网络 物联网 

分 类 号：TN99[电子电信—信号与信息处理] TP277[电子电信—信息与通信工程]