Fast and Robust Temperature-Dependent Three-Phase State Estimation Using Hierarchical Constrained Optimization

This article presents a robust and computationally efficient three-phase power system state estimation method that incorporates bus voltage phasors and line conductor temperatures as state variables for a large-scale power network. The proposed approach utilizes both conventional and synchronized phasor measurements together with heat-balance equations derived from weather data on transmission lines. The state estimation is formulated as a constrained nonlinear optimization problem. A hierarchical constrained optimization strategy is introduced, which decomposes an entire power system into the primary subnetwork at the top level and the lower-level unconnected multi-subnetworks. Only the primary subnetwork shares boundary buses with the lower subnetworks. The estimated boundary bus voltage phasor states obtained from the primary subnetwork are served as additional equality constraints for solving the remaining subnetworks. There is no need for a local slack bus in each lower-level subnetwork. This separation allows for parallel processing of the lower-level subnetworks, which enhances overall computational efficiency. The proposed state estimator is implemented and evaluated on a modified IEEE 118-bus system, adapted into an unbalanced three-phase network. Results demonstrate a significant improvement in computational efficiency and estimation accuracy.