基于智能电表数据的低压配电网拓扑与线路参数联合辨识OACSTPCD

In the low-voltage distribution network,frequent extensions and modifications by users lead to the issues such as delayed information updates and missing data in the account,making it difficult to obtain the topology and line parameters under the current operating conditions.For low-voltage distribution networks that lack phase angle measurement information and include an indeterminate number of"hidden nodes"with zero injection power,this paper presents a method for joint identification of the network topology and line parameters utilizing data from smart meters.Based on the electrical and structural characteristics of radial low-voltage distribution network,a linear inverse power flow model in the form of power-to-voltage ratio is derived.The impedance distance matrix is obtained by linear regression solution,and then the topology and line parameters are jointly identified using an improved recursive grouping algorithm without threshold setting.Finally,the effectiveness of the proposed algorithm is verified by arithmetic simulation in the IEEE European low-voltage test feeder and an actual low-voltage distribution network in Nanjing,China.