摘要
针对传统配电网三相不平衡动态状态估计存在计算速度较慢且估计精度较低的问题,提出了一种基于高级量测体系(AMI)全量测点分区的配电网的动态状态估计方法。以AMI全量测点作为配电网分区节点,提出综合3个指标的分区目标函数对配电网进行分区,可对子区域进行完全解耦,缩小系统规模;并通过所提数据融合框架进行多尺度量测数据的融合,以远程终端单元量测周期为基准,融合量测周期较长的AMI量测数据,对非AMI量测时刻的系统状态进行跟随。提出一种基于子区域数据融合方法的高精度集合卡尔曼滤波算法,采用协方差膨胀法改进滤波发散的问题。算例仿真结果表明所提方法有效地提高了配电网动态状态估计的计算速度和估计精度。
Aiming at the problems of slow calculation speed and low estimation accuracy of traditional threephase unbalance dynamic state estimation of distribution network,a dynamic state estimation method based on partition of advanced metering infrastructure(AMI)total measurement points is proposed.Taking the AMI total measurement points as the partition nodes of distribution network,the partition objective function integrating three indexes is put forward to partition the distribution network,which can completely decouple the sub-regions and reduce the system scale.The multi-scale measurement data is fused through the proposed data fusion framework.Based on the measurement cycle of the remote terminal unit,the AMI measurement data with a long measurement cycle is fused and the system state at non-AMI measurement time is fol⁃lowed.A high-precision ensemble Kalman filtering algorithm based on sub-region data fusion is proposed and the covariance expansion method is used to improve the divergence problem of filter.The simulative results show that the proposed method can effectively improve the calculation speed and estimation accuracy of distribution network dynamic state estimation.
作者
王云静
邢奥岚
曲正伟
辛松林
郭垲
WANG Yunjing;XING Aolan;QU Zhengwei;XIN Songlin;GUO Kai(Hebei Provincial Key Laboratory of Power Electronics for Energy Conservation and Drive Control,Yanshan University,Qinhuangdao 066004,China;Beijing Shougang Co.,Ltd.,Beijing 100041,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2023年第7期142-150,共9页
Electric Power Automation Equipment
基金
国家自然科学基金资助项目(51807172)。
关键词
配电网
高级量测体系
数据融合
动态状态估计
集合卡尔曼滤波
量测点分区
distribution network
AMI
data fusion
dynamic state estimation
ensemble Kalman filtering
partition of measurement points