Title :
Detection Of Power Quality Disturbances Using Deformation Tensor Parameters
Author :
Arias, Santiago ; Ustariz, Armando Jaime ; Cano, Eduardo Antonio
Author_Institution :
Univ. Nac. de Colombia, Bogota, Colombia
fDate :
7/1/2015 12:00:00 AM
Abstract :
This paper introduces a new segmentation algorithm of voltage waveforms. This new algorithm uses the strength of the tensor concept of the voltage signals to generate a unique pattern of deformation in three-phase systems. This deformation pattern is used to perform segmentation by detecting residues. In the process of segmentation, a modification to the Kalman filter has been proposed based on the work presented by Rakhee Panigrahi and Cesar Duarte. With this modification, we have obtained a robust response with a term included for estimating adaptively to sudden changes in the system. Additionally, it has been implemented a strategy of adaptive thresholding to adapt to noisy signals. This segmentation strategy is validated using a set of synthetic signals with variation of the remnant voltage and the starting point of the disturbance. Finally, the proposed algorithm is tested with a set of real signals.
Keywords :
Kalman filters; deformation; power supply quality; power system faults; Kalman filter; adaptive thresholding; deformation pattern; deformation tensor parameters; noisy signals; power quality disturbances; remnant voltage; segmentation algorithm; synthetic signals; tensor concept; three-phase systems; voltage signals; voltage waveforms; Color; Covariance matrices; Kalman filters; Media; Power quality; Robustness; Tensile stress; Adaptive kalman filter; Adaptive threshold; Electromagnetic perturbations; Segmentation; Tensor analysis; Voltage sags;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2015.7273765