智能电网监控运行大数据分析系统总体设计

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。文中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。

General Design of Smart Grid Monitoring Operation Big Data Analysis System

The monitoring data of power grid has characteristics of multiple sources, high dimensional, prior and hierarchical structure. Traditional power grid monitoring operation analysis technologies relying on artificial experience have been unable to meet the development requirements of centralized control and integration operation of bulk power system. It is necessary to achieve efficient collection and information mining in the power grid monitoring, to improve the ability of dispatchers to actively detect the real-time operation status of the power grid. By analyzing 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 puts forward to the technology line of data to model and model to application based on monitoring analyzing requirements. On the other hand, this paper designs the overall framework covering the bottom-up application of data access to business, and establishes a statistical analysis center, trend warning center, intelligent search, visualization exhibition center. It has made a breakthrough in standardizing data access, the whole process of data processing and the causal modeling technology, and a management model has been formed, which is 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 operation status of the demonstration project.