An improved algorithm for power system fault type classification based on least square phasor estimation

Smart grids have urged a radical reappraisal of distribution networks and power quality requirements, which demand to continuously monitor grid conditions. This allows for early classification of power quality degeneration. In this context, this paper proposes an improved algorithm for phasor estimation and fault type classification in smart grid applications. The proposed algorithm is specifically composed of two steps: first, the phasor estimation from the input signals, which can be executed on the Phasor Measurement Unit (PMU). While step two concerns the fault type classification using the phasor estimation. Specifically, we propose to estimate the phasor parameters, (frequency, amplitude and initial phase) using least square method. Then, fault type classification is obtained using symmetrical component algorithm. The proposed algorithm can be used for the identification of power quality disturbances. It has been evaluated, compared, and studied with simulated data. Simulation results show accurate phasor estimations and accurate fault type classification in presence of noise.