Temperature-dependent state estimation based on constrained alternating optimization for three-phase power networks considering transformer parameters

Abstract

This paper presents a three-phase power system state estimation method based on weighted least square criteria in which not only bus voltage phasors but also transformer parameters, i.e. its tap ratio and leakage admittance, as well as overhead transmission line conductor temperatures are considered as state variables. The method integrates the admittance matrix model of three-phase transformers and a weather dependent thermal model of the overhead transmission lines into the power system state estimation process, which is then formulated as a constrained nonlinear optimization problem. A solution technique based on constrained alternating optimization, suitable for the temperature-dependent state estimation considering the transformer’s parameters, is also proposed. The state estimation optimization is divided into two constrained sub-optimization problems, which are solved alternately until convergence conditions are satisfied. A predictor–corrector interior point based algorithm is applied for solving the sub-optimization problems. Several tests on modified IEEE 30-bus and 118-bus systems configured as three-phase test systems indicate that the proposed temperature-dependent state estimation significantly outperforms traditional methods.