A New Robust Identification Method for Transmission Line Parameters Based on ADALINE and IGG Method

Abstract

Accurate transmission line parameters are the basis of power system calculations. Aiming at obtaining accuracy online transmission line parameters in the case of large random noises even bad data in Phasor Measurement Unit (PMU) measurements, which occurs frequently in the practice, a new adaptive robust identification method combining adaptive linear neuron (ADALINE) and traditional robust IGG (Institute of Geodesy & Geophysics, Chinese Academy of Sciences) method is proposed. In detail, first, the identification model of transmission line parameters is presented based on the multi-period PMU measurements at both ends of the transmission line. Then, a parameter solving model based on ADALINE is established. Furthermore, to fully use measurement information, the adaptive robust ADALINE (ARA) are proposed, which applies the robust IGG weight function (Scheme I) to ADALINE to realize “three segments” robust identification. In addition, to improve the robustness, the expectation and variance of the equation residual sequence are estimated adaptively with the median principle to adjust the threshold for the IGG function to assure robustness (TAR), which is independent of the known information for the error of the measurement equipment. The cases based on PSCAD simulated data and measured data show the effectiveness and engineering practicality of the proposed method.

Keywords

• PMU
• ADALINE
• robust IGG
• transmission line parameters identification
• bad data
• median estimation