Robust linear state estimation for large multi-area power grids

摘要

This paper focuses on state estimation in very large systems with several control areas where there are sufficient phasor measurement unit (PMU) measurements to allow implementation of a linear state estimator. The paper exploits the natural partitioning of the grid by control areas and develops an estimation framework based on the well-known Dantzig-Wolfe decomposition principle for linear programming problems. The objective of this approach is to fully utilize PMU measurements, achieve robustness against bad data irrespective of their locations and develop a solution algorithm whose computational performance will remain insensitive to the number of control areas in a large multi-area power grid. Problem formulation, derivation of the solution algorithm and sample results illustrating its performance are presented.