摘要
为解决当前换流站在线监测系统在运行中存在的可靠性、安全性以及误告警频发等问题,文中基于泛在电力物联网技术对系统进行优化重构。首先,通过构建平台层,将系统接入物联管理平台以及数据中台,实现数据的融通共享,减轻云端存储压力,提升服务响应。其次,设计基于边缘计算的物联智能终端,实现站内设备的安全接入和泛在物联,该装置作为边缘计算节点通过集成深度学习算法,实现站端数据的采集存储、计算分析与异常识别,提高了告警的准确性和系统运行的可靠性。因此,基于泛在电力物联网的换流站在线监测系统架构优化为后续工程实践提供了一种新的建设应用模式。
In order to solve the problems of reliability,safety and frequent false alarms in the current operation of the online monitoring system of converter station,a system based on the ubiquitous power IoT advanced technology is reconstructed in this paper.By constructing the platform layer,the system is connected to the IoT management platform and the enterprise mid-station,which realizes the fusion sharing of DC device operation data,reduces the cloud data storage pressure and improves the system service response.Secondly,the intelligent terminal based on the edge computing framework to realize the safe access and ubiquitous connection of various online monitoring devices is designed.The device is deployed as an edge computing node,integrating the algorithm of deep learning to realize the station-side data acquisition,storage,analysis and anomaly identification,which improves the accuracy of the alarm and system operation reliability.Therefore,the optimization of the online monitoring system architecture of the converter station based on the ubiquitous power IoT provides a typical application model for subsequent engineering practice.
作者
吕继伟
LYU Jiwei(State Grid Co.,Ltd.DC Technology Center,Beijing 100052,China)
出处
《电力工程技术》
2019年第6期9-15,共7页
Electric Power Engineering Technology
关键词
泛在电力物联网
边缘计算
在线监测
深度学习
换流站
ubiquitous power internet of things
edge computing
online monitoring
deep learning
converter station
作者简介
吕继伟(1987),男,硕士,工程师,从事电网调控自动化、信息化运行管理工作(E-mail:jiwei_lv@163.com)。
