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Differential Evolution Implementation for Power Quality Disturbances Monitoring using OpenCLSOLIS-MUNOZ, F. J. , OSORNIO-RIOS, R. A. , ROMERO-TRONCOSO, R. J. , JAEN-CUELLAR, A. Y.
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evolutionary computation, parallel programming, parallel processing, power quality, power system faults
power(29), comput(14), optimization(13), quality(10), evolution(10), algorithm(10), systems(9), parallel(9), energy(9), soft(7)
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About this article
Date of Publication: 2019-05-31
Volume 19, Issue 2, Year 2019, On page(s): 13 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.02002
Web of Science Accession Number: 000475806300002
SCOPUS ID: 85066330466
This article presents a new methodology to implement a computational parallel scheme based on Differential Evolution (DE) algorithm through the use of Graphical Processing Units (GPU). A system application in which it is possible to perform an online monitoring of Power Quality Disturbances (PQD) in electric grids is presented as a case study, where a fitting of the parameters of a mathematical model is performed through this technique. Hyper-parameter optimization of the parallel Differential Evolution algorithm is performed for the assigned fitting function. As a result of this parallel implementation, a speed-up of 37 times compared with the serial implementation is achieved by using a single low budget GPU. The work presented shows a significant speed and accuracy improvement compared with Micro-Genetic Algorithm for Power Quality Analysis (MGA-PQA) technique.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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