Abstract:In order to solve the problems of large number of front-end data, data-missing and complex analysis, this paper proposes a state estimation algorithm suitable for active distribution network to manage the analysis data. This paper proposes an active distribution network state estimation algorithm based on decision tree self-identification. By estimating the pre-processed data, classifying and correcting the data, the data in the input state estimation model is better compatible. At the same time, this paper establishes a state estimation model considering distributed power supply for the problem of less distributed energy measurement equipment, and supplements the distributed energy default data to improve the quality of input data. The method can be verified in the actual example. Compared with the traditional state estimation, the active distribution network state estimation algorithm based on decision tree self-identification has better estimation effect and faster iteration speed. Therefore, the proposed algorithm can be effectively applied to the current state estimation of large-scale distributed energy access.