Distributed state estimation for condition monitoring of nonlinear electric power systems

The paper analyzes distributed state estimation based on the Extended Information Filter (EIF) and on the Unscented Information Filter (UIF), aiming at developing tools for systematic condition monitoring of the electric power distribution system. It is considered that the complete state vector of the power system is unavailable and only indirect voltage measurements can be obtained. With the use of filtering algorithms running on processing units located at different parts of the power grid, one can produce local estimates of the system's state vector. Moreover, to improve the estimation accuracy and the reliability of data processing, fusion of the distributed state estimates is performed with the use of the EIF and UIF aggregation filter. The produced state estimates enable continuous monitoring of the condition of the power distribution system.