文章摘要
冷喜武,陈国平,白静洁,等.智能电网监控运行大数据分析系统总体设计[J].电力系统自动化. DOI: 10.7500/AEPS20170920002.
LEN Xiwu,CHEN Guoping,BAI Jingjie, et al.General Design of Smart Power Grid Monitoring Operation Big Data Analysis System[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20170920002.
智能电网监控运行大数据分析系统总体设计
General Design of Smart Power Grid Monitoring Operation Big Data Analysis System
DOI:10.7500/AEPS20170920002
关键词: 监控大数据  规范化数据接入  全过程数据处理  大数据因果分析
KeyWords: monitoring big data  standardized data access  whole process data processing  Big data cause and effect analysis.
上网日期:2018-05-14
基金项目:
作者单位E-mail
冷喜武 国家电网公司 xiwu-leng@sgcc.com.cn 
陈国平 国家电网公司 chen-guoping@sgcc..com.cn 
白静洁 北京科东电力控制系统有限责任公司 baijingjie@sgepri..com.cn 
张家琪 国网物资有限公司 zhangjiaqi@sgm.sgcc..com.cn 
摘要:
      电网监控数据具有多源、高维、先验、异构的特点,传统依靠人工经验的电网监控运行分析技术已无法满足大电网集中调控、一体化运行的发展要求,需要实现电网监控运行全过程信息的高效汇集和智能挖掘分析,以提高监控人员对电网实时运行状态的主动感知能力。本文通过分析现有业务系统在数据规范和分析手段等方面的局限性,阐明了建设智能电网监控运行大数据分析系统的必要性,提出了以监控业务需求为引领的“数据到模型,模型到应用”的技术路线,设计了涵盖数据接入至业务应用自下而上的整体架构,构建了统计分析中心、趋势预警中心、智能搜索中心及可视化展示中心的功能体系,取得了规范化数据接入、全过程数据处理及大数据因果分析建模等关键技术的突破,形成了事前异常趋势预警,事中快速处置和事后闭环分析的管理模式。根据示范工程的建设和试点运行情况,介绍监控运行大数据分析系统在数据规范处理、业务分析建模和监控业务管理方面的应用成效及未来应用展望。
Abstract:
      The monitoring data of grid has power big data characteristics of multiple sources, high dimensional, prior and heterogeneous. Relying on traditional artificial experience of power system monitoring analysis technology have been unable to meet the requirements of centralized control and integration of power grid development, which need to im-plement the whole process of information collection of efficient monitoring of power grid and intelligent mining analysis, in order to improve the monitoring personnel for grid real-time operation state of active perception. By an-alyzing the limitations of the existing business system in terms of data specification and analysis methods, this paper illustrates the necessity of the construction of the monitoring system of smart grid operation data. At the same time, this paper put forward to the technology line of data to model and model to application which based on monitoring analyzing requirements. On the other hand, this paper designs the overall framework covering the bottom-up appli-cation of data access to business, and establishes a statistical analysis center, trend warning center, intelligent search and visualization center and exhibition center. In the end, it has made a breakthrough in standardizing data access, the whole process of data processing and data analysis of causal modeling, and a management model has been formed, which made up of the formation of abnormal trend prior warning, rapid response and post analysis in closed loop. This paper introduces the effects of standardized data processing, business modeling and monitoring management on the basis of the construction and running state of the demonstration project.
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