事件触发机制下配电网三相动态状态估计  

Three-phase Dynamic State Estimation for Distribution Network in Event-triggered Mechanism

作　　者：黄蔓云[1] 徐启颖 孙国强[1] 卫志农[1] 孙康 HUANG Manyun;XU Qiying;SUN Guoqiang;WEI Zhinong;SUN Kang(School of Electrical and Power Engineering,Hohai University,Nanjing 211100,China)

机构地区：[1]河海大学电气与动力工程学院,江苏省南京市211100

出　　处：《电力系统自动化》2024年第13期100-108,共9页Automation of Electric Power Systems

基　　金：国家自然科学基金青年科学基金资助项目(52207090)。

摘　　要：随着高级量测体系的发展和智能电表的广泛应用,为配电网三相状态估计提供了丰富的终端量测信息。与此同时,大量的智能电表数据给配电网通信系统提出了更高的通信带宽和实时存储要求。为了缓解量测拥堵和时延现象,文中引入事件触发机制代替传统量测数据的周期性采样,在保证有效量测信息及时上传的同时减少通信成本和投资。在此基础上,针对配电网实时状态感知问题,提出了基于鲁棒集合卡尔曼滤波的配电网三相动态状态估计方法,在正常运行场景下,能够保持与无偏估计加权最小二乘法相近的估计精度;当含有坏数据时,该方法也拥有较强的鲁棒性。With the development of advanced metering infrastructure and the wide application of smart meters,the rich terminal measurement information is provided for the three-phase state estimation of distribution networks.At the same time,a large amount of smart meter data puts forward higher communication bandwidth and real-time storage requirements to the communication system of distribution networks.In order to alleviate the phenomenon of the measurement congestion and delay,this paper introduces an event-triggered mechanism instead of the traditional periodic sampling of measurement data,which ensures the timely uploading of effective measurement information while reducing the communication cost and investment.On this basis,for the real-time state sensing problem of distribution network,this paper proposes a three-phase dynamic state estimation method based on the robust ensemble Kalman filter,which can maintain estimation accuracy similar to the weighted least squares method in normal operation scenarios.The method also possesses strong robustness against bad data.

关 键 词：配电网 状态估计 事件触发机制 集合卡尔曼滤波 加权最小二乘法 

分 类 号：TM73[电气工程—电力系统及自动化]