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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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Author keywords
evolutionary computation, parallel programming, parallel processing, power quality, power system faults
References keywords
power(29), comput(14), optimization(13), quality(10), evolution(10), algorithm(10), systems(9), parallel(9), energy(9), soft(7)
Blue keywords are present in both the references section and the paper title.
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
Abstract
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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