电网调控集群分布式实时数据库的设计与关键技术

WU Qingxi

您当前的位置：

首页 >

文章列表页 >

电网调控集群分布式实时数据库的设计与关键技术

更新时间：2025-08-13

- 电网调控集群分布式实时数据库的设计与关键技术
- Automation of Electric Power Systems Vol. 41, Issue 22, Pages: 89-95(2017)
- 作者机构：
  
  南瑞集团公司(国网电力科学研究院),江苏省,南京市,211106
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
WU Qingxi. [J]. Automation of electric power systems, 2017, 41(22): 89-95.
DOI：

WU Qingxi. [J]. Automation of electric power systems, 2017, 41(22): 89-95. DOI：

摘要

为解决电网调度控制系统大规模实时数据的处理性能问题，设计了一种集群分布式实时数据库，通过分布式技术实现海量数据存储，并使用集群技术实现数据的统一访问和管理。对集群分布式实时库架构及所使用的分布式存储技术、分布式数据定位技术和分布式访问技术进行了讨论，解决了调度控制系统实时数据的灵活分片、分布式存储和快速定位问题。最后通过测试和现场运行验证了集群分布式实时数据库能在确保系统高可靠性的条件下，实现实时数据的高性能访问。

Abstract

In order to solve the problem of processing performance of large-scale real-time data in power dispatching and control systems

a cluster based distributed real-time database is designed

which uses distributed technologies to achieve massive data storage and cluster technologies to achieve uniform data access and management. Key technologies of cluster based real-time database are discussed including distributed storage

distributed data location and distributed data access. The problem of flexible slicing

large-scale data storage and fast data locating of real-time data in a power dispatching and control system is also solved. Testing and on-site system verification prove that the cluster based distributed real-time database system is able to achieve high efficient data access and the condition of high reliability of the system is ensured.

关键词

Keywords

references

Views

2388

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Preliminary Study on Spatial Complementarity Characteristics of Short-term Power Prediction for Distributed Photovoltaic Clusters

Operation Data Based Analysis on Complementary Characteristics of Short-term Power Prediction Error for Wind Power

大电网全局监控内涵与关键技术

Related Author

HUANG Chunyi

LI Zhenghui

LI Kangping

RUAN Chenglong

Yanan SUN

Yuehui HUANG

Yiqian SUN

Xiqiang CHANG

Related Institution

College of Smart Energy, Shanghai Jiao Tong University

Shanghai Non-carbon Energy Conversion and Utilization Institute

Department of Electrical Engineering, Tsinghua University

Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Shanghai Jiao Tong University)

State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (China Electric Power Research Institute)

⁰