Bilinear WLAV power system state estimation based on interior point method

Traditional weighted least absolute value (WLAV) rubust state estimation based on interior point method (IPM) can improve the estimation accuracy by minimizing the impact of bad datas which is limited in practical application because of low efficiency. In this paper, a bilinear weighted least absolute value (WLAV) power system state estimation (SE) based on interior point method is proposed, where the introducing of intermediate variables transfers the nonlinear measurements functions into two linear equations with two nonlinear transformation in between. The computation of Hessian matrix in correction equation is avoided and the dimention of coefficient matrix in Karush-Kuhn-Tucker (KKT) condition is reduced when applying the interior point algorithm to solve the linear equations. Finally, compared with the traditional method, it follows from the simulation results that the proposed method possesses better computational efficiency and estimating precision.