Robust state estimation for distribution networks based on residual prediction

In order to improve the calculation accuracy and speed of distribution networks state estimation, this paper presents a robust algorithm of three-phase state estimation for distribution networks based on residual prediction. All kinds of measurements in distribution networks are used in the algorithm, jacobian matrix becomes constant though phase transform of node voltage and branch current, and equivalent transform of current amplitude measurement, the amount of calculation is reduced due to jacobian matrix remains unchanged in the iterative process. Setting of quivalent weight based on prediction residual avoids the unnecessary iterations in the correction of the equivalent weight, which reduces the amount of computation. Simulation results have shown the proposed method in this paper is stable and robust.