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Estimate the electromechanical states using particle filtering and smoothing

Accurate knowledge of electromechanical states is critical for efficient and reliable control of a power system. This paper proposes a particle filtering approach to estimate the electromechanical states of power systems from Phasor Measurement Unit (PMU) data. Without having to go through a laborious linearization procedure, the proposed particle filtering techniques can estimate states of a complex power system, which is often non-linear and has non-Gaussian noise. The proposed method is evaluated using a multi-machine system and its responses. Sensitivity studies of the dynamic state estimation performance are also presented to show the robustness of the proposed method. A promising path forward for the application of the proposed method is to reduce computational time through efficient parallel implementation owing to the inherent decoupling properties of particle filtering.