许洪强, 孙世明, 葛朝强, 屈刚, 孙云枫, 王兴志, 孙文彦. 电网调控实时数据平台体系架构及关键技术研究与应用[J]. 电力系统自动化, 2019, 43(22): 157-164.
引用本文: 许洪强, 孙世明, 葛朝强, 屈刚, 孙云枫, 王兴志, 孙文彦. 电网调控实时数据平台体系架构及关键技术研究与应用[J]. 电力系统自动化, 2019, 43(22): 157-164.
XU Hongqiang, SUN Shiming, GE Zhaoqiang, QU Gang, SUN Yunfeng, WANG Xingzhi, SUN Wenyan. Research and Application of Architecture and Key Technologies for Power Grid Real-time Dispatching and Control Data Platform[J]. Automation of Electric Power Systems, 2019, 43(22): 157-164.
Citation: XU Hongqiang, SUN Shiming, GE Zhaoqiang, QU Gang, SUN Yunfeng, WANG Xingzhi, SUN Wenyan. Research and Application of Architecture and Key Technologies for Power Grid Real-time Dispatching and Control Data Platform[J]. Automation of Electric Power Systems, 2019, 43(22): 157-164.

电网调控实时数据平台体系架构及关键技术研究与应用

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

  • 摘要: 一体化运行的互联大电网对现有调度自动化系统实时数据的全局性和实时性等提出了新的挑战,文中提出了电网调控实时数据平台体系架构和建设目标原则。在此基础上,研究了电网模型在线同步、分布式数据汇集与处理、大规模并行状态估计、实时数据统一服务等关键技术,实现了基于模型自动同步免维护下的全网实时数据单点采集、全网共享。研发的电网调控实时数据平台在国分调控中心试点建设,应用结果表明,所提技术方案提高了实时数据汇集的全局性、实时性和运维效率,能够为电网分析决策应用提供全面、实时、准确的全网实时数据和状态估计数据断面。

     

    Abstract: 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.

     

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