Research Article
Power Quality Analysis Using Higher-Order Statistical Estimators: Characterization of Electrical Sags and Swells
@INPROCEEDINGS{10.1007/978-3-642-32304-1_3, author={Juan Gonz\^{a}lez de la Rosa and Agust\^{\i}n p\^{e}rez and Jos\^{e} Palomares-Salas and Jos\^{e} Fern\^{a}ndez and Jos\^{e} Ramiro Leo and Daniel Sede\`{o}o and Antonio Moreno-Mu\`{o}oz}, title={Power Quality Analysis Using Higher-Order Statistical Estimators: Characterization of Electrical Sags and Swells}, proceedings={IT Revolutions. Third International ICST Conference, C\^{o}rdoba, Spain, March 23-25, 2011, Revised Selected Papers}, proceedings_a={IT REVOLUTIONS}, year={2012}, month={10}, keywords={Higher-Order Statistics (HOS) Power-Quality (PQ) Sag Swell}, doi={10.1007/978-3-642-32304-1_3} }- Juan González de la Rosa
Agustín pérez
José Palomares-Salas
José Fernández
José Ramiro Leo
Daniel Sedeño
Antonio Moreno-Muñoz
Year: 2012
Power Quality Analysis Using Higher-Order Statistical Estimators: Characterization of Electrical Sags and Swells
IT REVOLUTIONS
Springer
DOI: 10.1007/978-3-642-32304-1_3
Abstract
This work presents the detection results involving two common electrical disturbances: sags and swells. Variance, skewness and kurtosis have been used to improve statistical characterization. The measurement procedure is funded in the tuning of the signal under test via a sliding window over which computation is developed. Locking is possible because these power quality disturbances keep the frequency of the power line. Statistical features reveal the inherent properties of the signals: amplitude, frequency and symmetry. The paper primarily examines a number of synthetics in order to extract the theoretical statistical features. Then the algorithm is corroborated using real-life signals, obtaining an accuracy of 83%. This stage is part of the design of an instrument for the measurement of the power quality.