State Estimation in Unbalanced Distribution Networks by Symmetrical Components

Abstract

State estimation (SE) of a power distribution network plays a vital role in the distribution management systems (DMSs). SE results can monitor and counteract grid technical challenges like tracking the unbalanced operation condition. In this paper, we propose a new approach for unbalanced distribution system SE which is based on the decomposition of the original problem into three subproblems by applying the symmetrical components. The subproblems are of lower dimensions and solved in parallel leading to much less computation time. The convex relaxation method is applied to address nonconvex ac power flow equations and formulate the distribution network SE problem as a semidefinite program (SDP). Furthermore, an algorithm is proposed to detect and attenuate bad data in measurements along with the SE solution. The proposed unbalanced distribution system SE approach is applied to the IEEE 37-and 123-node distribution test systems. The results are compared with those of three-phase SDP-based and linearized SE methods. The superiority of proposed approach is verified in terms of computation time and accuracy.