• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2019, Vol. 40 ›› Issue (6): 123-131.doi: 10.3969/j.issn.1000-7229.2019.06.014

• 智能电网 • 上一篇    下一篇

基于DSCADA和μPMU数据融合的配电网运行拓扑辨识

王贺飞1,李洪涛2,余昆3,郭文鑫3,黄堃1   

  1. 1.南瑞集团有限公司(国网电力科学研究院有限公司),南京市211000;2.国网北京市电力公司,北京市 100031;3.河海大学能源与电气学院,南京市 210098
  • 出版日期:2019-06-01
  • 作者简介:王贺飞(1987),男,硕士,主要研究方向为配电自动化与电力系统控制技术; 李洪涛(1975),男,硕士,高级工程师,研究方向为智能配电网和配电网可靠运行技术; 余昆(1978),男,博士,副教授,通信作者,主要研究方向为智能配电网自愈控制与优化调度、配用电系统多能互补与高效运行技术; 郭文鑫(1994),男,硕士研究生,主要研究方向为配电网协调控制技术。
  • 基金资助:
    国家电网公司科技项目(适应电能替代规模化应用的配电网建设改造关键技术研究)

Identification of Distribution Network Operation Topology Based on DSCADA and μPMU Telemetry Data Fusion

WANG Hefei1,LI Hongtao2,YU Kun3,GUO Wenxin3,HUANG Kun1   

  1. 1.NARI Group Corporation (State Grid Electric Power Research Institute,Nanjing 211000,China);2. State Grid Beijing Electric Power Company,Beijing 100031,China;3. College of Energy and Electrical Engineering,Hohai University, Nanjing 210098,China
  • Online:2019-06-01
  • Supported by:
    This work is supported by State Grid Corporation of China Research Program.

摘要: 在配电网安装了配电网数据采集及监视控制系统(distribution network supervisory control and data acquisition, DSCADA)和部分节点安装少量微型同步相量测量装置(micro-synchronous phasor measurement unit, μPMU)情形下,提出了一种基于DSCADA和μPMU遥测数据融合的配电网运行拓扑辨识方法。首先,基于μPMU节点电压相位量测构建配电网拓扑变化时刻辨识模型,确定拓扑变化的时刻;然后,基于拓扑变化前后的节点电压变化,借助DSCADA和μPMU的遥测数据构建可能拓扑判据,缩小重构后可能拓扑的范围;最后,使用加权最小二乘法将DSCADA和μPMU遥测数据进行融合,估计出可能拓扑下的节点电压相位,并利用构建的拓扑相似度辨识模型辨识出实际拓扑。算例中考虑μPMU和DSCADA不同量测误差组合,对该算法辨识的准确性进行验证。

关键词: 配电网, 拓扑辨识, 多源数据融合, 配电网数据采集及监视控制系统(DSCADA), 微型同步相量量测装置(&mu, PMU)

Abstract: In the case of distribution  network, distribution network supervisory control and data acquisition (DSCADA) system and a small number of micro synchronous phasor measurement units (μPMU) installed in some nodes of distribution network, a method for distribution network operation topology identification based on the fusion of DSCADA and μPMU telemetry data is proposed. Firstly, the identification model of topology change time is constructed on the basis of node voltage phase measurement by μPMU, and the time of topology change is identified. Then, on the basis of the node voltage changes before and after the topology changes, criteria for possible topologies is constructed with the help of DSCADA and μPMU telemetry data, and the possible range of the reconstructed topology is reduced. Finally, the weighted least squares method is used to fuse the DSCADA and μPMU telemetry data, to estimate the node voltage phase under the possible topologies, and to identify the actual topology by using the established topology similarity identification model. The accuracy of the algorithm is verified by considering different measurement error combinations of μPMU and DSCADA.

Key words: distribution network, topology identification, multi-source data fusion, distribution network supervisory control and data acquisition(DSCADA), micro-synchronous phasor measurement unit(μPMU)

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