Reverse identification method of line parameters in distribution network with multi-T nodes based on partial measurement data

Abstract Reverse identification of line parameters plays an important role in the calculation and analysis of the power grid, However, based on the absence of many original line parameters and much measurement data, the line parameter estimation that employs the common methods (such as the least squares method) may be unsatisfactory or even unachievable. Hence, this paper proposes a reverse identification method of line parameters in the distribution network with multi-T nodes based on partial measurement data of the SCADA and the μPMU. Without many original values of line parameters, a multi-time reverse identification model of line parameters is established. The model is solved by the differential evolution algorithm, which is employed to realize accurate identification. The proposed method is tested based on 110 kV, 35 kV, and 10 kV distribution network cases, and the results show that the proposed method can realize precise identification under the conditions of lacking many original parameters and all measurement data of T-connection nodes.