DocumentCode
3498266
Title
Embedded power quality monitoring system based on Independent Component Analysis and SVMs
Author
Ruiz-Llata, Marta ; Guarnizo, Guillermo ; Boya, Carlos
Author_Institution
Dept. of Electron. Technol., Univ. Carlos III de Madrid, Leganés, Spain
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
2229
Lastpage
2234
Abstract
On-line identification and classification of voltage and current disturbances in power systems are important tasks in the power quality monitoring and protection of power systems. Some power quality disturbances are non-stationary and transitory while other are steady-state variations that distort the voltage signal. One, two or more different power quality disturbances may appear at the same time. In this paper we propose a power quality monitoring system that employs Independent Component Analysis algorithm that is able to decouple multiple simultaneous power quality disturbances, and Support Vector Machines for identification the occurrence of a disturbance. We also show the first steps towards embedding the proposed system on an FPGA for online power quality monitoring.
Keywords
field programmable gate arrays; independent component analysis; power engineering computing; power supply quality; power system faults; power system identification; power system measurement; power system protection; support vector machines; SVM; current disturbance; embedded power quality monitoring system; independent component analysis algorithm; power quality disturbance; power system protection; support vector machine; voltage disturbance; voltage signal distortion; Harmonic analysis; Kernel; Monitoring; Power harmonic filters; Power quality; Support vector machines; Transient analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location
San Jose, CA
ISSN
2161-4393
Print_ISBN
978-1-4244-9635-8
Type
conf
DOI
10.1109/IJCNN.2011.6033506
Filename
6033506
Link To Document