基于分布式文件系统的海量电能质量监测数据管理方案

发布时间：2018-01-07 16:12

本文关键词：基于分布式文件系统的海量电能质量监测数据管理方案　出处：《电力系统自动化》2014年02期 　论文类型：期刊论文

【摘要】：目前,电能质量监测数据已经呈现海量化的趋势,如果仅用关系数据库存储,将带来存储占用空间大、存取速度慢、可扩展性差等问题。文中通过分析现有电能质量监测系统中的数据存取特征和硬件环境,提出了一种基于分布式文件系统的海量电能质量监测数据管理方案。此方案将不同电能质量指标的历史监测数据分别压缩后存储在文件中;利用现有监测子站以及相关系统的分布式异构服务器作为文件服务器以存储数据文件;利用监测主站服务器作为主服务器,保存数据特征值和文件索引,并对文件资源进行统一管理。此方案充分利用了各服务器的存储空间和网络带宽,节约了存储空间,提高了存取效率,具有较高的可靠性和可扩展性。以存储100个监测点180 d数据为例,此方案存储空间占用仅为传统关系数据库方案的2.28%;以检索某个监测点180 d的5次谐波三相电压幅值数据为例,此方案加速比约为16.49倍。在四川电能质量一体化数据平台中的成功应用证明了此方案的可靠性和实用性。
[Abstract]:At present, power quality monitoring data has shown the trend of sea quantization. If only stored in relational database, it will lead to large storage space and slow access speed. This paper analyzes the data access characteristics and hardware environment of the existing power quality monitoring system. A massive power quality monitoring data management scheme based on distributed file system is proposed, in which the historical monitoring data of different power quality indicators are compressed and stored in the file. The existing monitoring substations and distributed heterogeneous servers of related systems are used as file servers to store data files; The monitoring master server is used as the master server to save the data characteristic value and file index, and to manage the file resources in a unified way. This scheme makes full use of the storage space and network bandwidth of each server. The storage space is saved, the access efficiency is improved, and the reliability and expansibility are higher. Take the 180 d data storage of 100 monitoring points as an example. The storage space occupied by this scheme is only 2.28% of the traditional relational database scheme. For example, the amplitude data of the fifth harmonic three-phase voltage at a monitoring point 180 d are retrieved. The speedup ratio of this scheme is about 16.49 times. The reliability and practicability of this scheme are proved by its successful application in Sichuan integrated power quality data platform.
【作者单位】：四川大学电气信息学院;四川电力科学研究院;
【基金】：国家自然科学基金资助项目(51077095)~~
【分类号】：TM73
【正文快照】： 0引言海量监测数据的管理已经成为各省级电能质量监测系统(以下简称“监测系统”)建设中需要解决的重要问题。数据海量化的原因主要包括以下两方面:一方面,电能质量监测指标(以下简称“指标”)数量众多,除了基本的电压、电流、频率外,还包括谐波、间谐波、三相不平衡、闪变以

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