基于多时间尺度状态估计的配电网实时态势预测

为有效提升泛在电力物联网建设过程中的配电网运行安全感知能力,提出了一种基于多时间尺度状态估计的配电网实时态势预测方法,该方法可实现对配电网安全态势的快速、准确预测。首先,基于多元混合量测提出了多时间尺度递归动态状态估计方法,通过状态预测与伪量测递归变换改进了已有的量测线性等效变换方法,缩短了状态更新周期,在递归变换算法中添加了校正算法以消除伪量测波动误差,提高了状态估计算法的计算速度。然后基于状态估计得到历史估计状态,采用分区多元时间序列分析方法建立了实时状态预测模型,实现了配电网的实时安全性态势预测。最后在Matlab仿真平台中基于实际算例对所提方法进行了分析,结果验证了所提配电网实时态势预测方法的准确性和有效性。

Real-time situation prediction of distribution network based on multi-time scale state estimation

Situational awareness technology is an important part of smart distribution networks. In order to effectively improve the situational awareness level of smart distribution network in China, this paper proposes a real-time situation projection method for distribution network based on multi-time-scale state estimation, which can reach a fast and accurate prediction of distribution network safety situation. A multi-time-scale recursive dynamic state estimation was realized based on hybrid measurement including distribution PMU through recursive transformation between state projection and pseudo measurement, which realizes the fast equivalent transformation of measurement and shorten the state update period. A correction module is added in the recursive transformation algorithm to eliminate pseudo-measurement fluctuation error, improving the stability and calculation speed of the state estimation algorithm. Real-time safety situation projection of distribution network was realized through partitioned multivariate time series analysis based on historic estimated states, which establishes a real-time state prediction model. Finally, practical examples was simulated and analyzed on MATLAB simulation platform. The simulation results validates the accuracy and effectiveness of the proposed real-time situation prediction method for distribution network.