Research and Application of Architecture and Key Technologies for Power Grid Real-time Dispatching and Control Data Platform

被引：0
|
作者：
Xu H. [1 ]
Sun S. [2 ,3 ,4 ]
Ge Z. [5 ]
Qu G. [5 ]
Sun Y. [2 ,3 ,4 ]
Wang X. [5 ]
Sun W. [2 ,3 ]
机构：
[1] National Electric Power Dispatching and Control Center, State Grid Corporation of China, Beijing
[2] NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing
[3] NARI Technology Co., Ltd., Nanjing
[4] State Key Laboratory of Smart Grid Protection and Control, Nanjing
[5] East China Branch of State Grid Corporation of China, Shanghai
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2019年 / 43卷 / 22期
基金：
国家重点研发计划;
关键词：
Distributed data processing; Online synchronization of power grid model; Original message collection; Parallel state estimation; Real-time data platform; Unified service of real-time data;
D O I：
10.7500/AEPS20190730004
中图分类号：
学科分类号：
摘要：
Integrated and interconnected bulk power grid puts forward new challenges to the global and real-time data of the existing dispatching automation system. This paper puts forward the architecture and construction principle of the power grid dispatching an control real-time data platform. On this basis, some key technologies such as online synchronization of power grid model, distributed data collection and processing, large-scale parallel state estimation, unified service of real-time data are studied. And single-point acquisition and sharing of real-time data in the entire network are realized based on automatic model synchronization without maintenance. The power grid real-time dispatching and control data platform is piloted in the national electric power dispatching and control subcenter. The application results show that the proposed scheme improves the globality, real-time capability, operation and maintenance efficiency of real-time data aggregation, and it could provide comprehensive, real-time and accurate snapshots of real-time data and state estimation data in the entire power grid for power grid analysis and decision-making applications. © 2019 Automation of Electric Power Systems Press.
引用
收藏
页码：157 / 164
页数：7
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