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电力大数据:2019,22(6):-
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基于监控大数据的设备监控业务评价指标体系的设计与实现
(1.国家电网公司;2.国网江苏省电力公司;3.国网淮安供电公司;4.国网南京供电公司)
Design and implementation of evaluation index system for equipment monitoring business based on monitoring big data
(1.State Grid Electric Power Company;2.State Grid Jiangsu Electric Power Company;3.State Grid Huaian Electric Power Company;4.State Grid Nanjing Electric Power Company)
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投稿时间:2018-07-09    修订日期:2018-12-28
中文摘要: 随着智能变电站的逐步覆盖,以及智能电网监控运行大数据分析系统数据接入范围的扩大,监控大数据系统具备海量数据的基本特征。本文设计的基于监控大数据系统的调控机构设备监控业务评价指标体系,主要包括数据管理、业务指标计算、GIS展示等功能,其中业务指标计算是以全网设备运行数据为基础,业务指标的计算具备数据规模大、计算复杂的特点。为了解决海量数据的统计效率,系统采用去中心化的建设思路,设计采用分级复用、面向服务和内存计算策略的多级指标计算框架,实现各类监控业务指标的高效统计,能够满足系统快速响应的非功能性需求,同时结合面向服务的分布式架构设计,实现不同系统之间的数据贯通,提升设备监控的业务协同能力,系统具备良好的扩展性。
中文关键词: 监控大数据  分级复用  内存计算  面向服务  
Abstract:With the gradual coverage of intelligent substation and the expansion of the data access range of the large data analysis system of the smart grid monitoring and operation, the monitoring large data system has the basic characteristics of the massive data. The system mainly includes data management, calculation of business indicators, GIS display. The calculation of business indicators is based on the operation data of equipment in the whole network, and the calculation of business indicators has the characteristics of large-scale data and complex calculation. In order to solve the statistical efficiency of massive data, decentralization is adopted in the construction of the system, the system designs a multi-level index calculation framework of hierarchical reuse, service oriented and memory computing strategy to realize various kinds of monitoring service indicators. High efficiency statistics can meet the non functional requirements of the fast response of the system, and implementing data connection between different systems, enhancing business collaboration of equipment monitoring, and the system has good scalability through the design of service oriented distributed architecture.
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