Dynamic Parameter Identification Technology of Distribution Network Line Based on Dynamic Graph Model

The accurate physical parameters of distribution lines are important for power grid analysis, and are essential to the stable and economic operation of the distribution network. In view of the subjectivity and hysteresis of traditional distribution network topology parameter recognition methods, this paper proposes a Dynamic Bayesian Network (DBN)-based distribution line parameter estimation model. The influence of the external environment and distribution operating mode is considered in the model. According to the relations between the parameters and the influencing factors, a DBN model is established to simulate the dynamic characteristics of the line parameters. Then the BP algorithm is applied to infer distribution line parameters with the DBN model. Finally, a case study based on a 10kV single-connected distribution network is used to prove that the proposed model has high accuracy and robustness in parameter identification.