To solve the problem of small sample imbalance in state estimation of active distribution networks(ADNs),this paper proposes a robust forecasting-aided state estimation(FASE)method based on the improved synthetic minority oversampling technique(SMOTE)and particle filter(PF)of Prophet.The method enables state estimation of ADNs.Firstly,to handle the small-sample imbalance problem,a hash function is constructed based on the data features of the ADN and an optimization approach is proposed using the hash function for the Borderline-SMOTE+Tomek-Links algo-rithm.Secondly,considering the large amount of data and the stochastic output of distributed energy resources in ADNs,the Prophet prediction model is used for state estimation of ADNs,and a robust FASE method based on Prophet-PF is proposed for fast and accurate estimation of ADNs states.Finally,numerical simulations are conducted on standard IEEE 118-bus distribution network and a DTU 7k 47 distribution system to evaluate the proposed method.The results demon-strate that the proposed method has high accuracy and robustness,providing useful references for state estimation in ADNs.
关键词
主动配电网/预测辅助状态估计/少数过采样技术/哈希函数/Prophet/粒子滤波
Key words
active distribution network/forecasting-aided state estimation/synthetic minority oversampling technique/Hash function/Prophet/particle filter
维普
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