Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System
Motivated by the effects of deregulation over power quality and the subsequent need of new types of measurements, this paper assesses different implementations of an estimate for the spectral kurtosis, considered as a low-level harmonic detection. Performance of a processor-based system is compared...
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MDPI AG
2019-03-01
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Series: | Energies |
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Online Access: | http://www.mdpi.com/1996-1073/12/5/914 |
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author | María-Ángeles Cifredo-Chacón Fernando Perez-Peña Ángel Quirós-Olozábal Juan-José González-de-la-Rosa |
author_facet | María-Ángeles Cifredo-Chacón Fernando Perez-Peña Ángel Quirós-Olozábal Juan-José González-de-la-Rosa |
author_sort | María-Ángeles Cifredo-Chacón |
collection | DOAJ |
description | Motivated by the effects of deregulation over power quality and the subsequent need of new types of measurements, this paper assesses different implementations of an estimate for the spectral kurtosis, considered as a low-level harmonic detection. Performance of a processor-based system is compared with a field programmable gate array (FPGA)-based solution, in order to evaluate the accuracy of this processing function for implementation in autonomous measurement equipment. The fourth-order spectrum, with applications in different fields, needs advanced digital signal processing, making it necessary to compare implementation alternatives. In order to obtain reproducible results, the implementations have been developed using common design and programming tools. Several characteristics of the implementations are compared, showing that the increasing complexity and reduced cost of the current FPGA models make the implementation of complex mathematical functions feasible. We show that FPGAs improve the processing capability of the best processor using an operating frequency 33 times lower. This fact strongly supports its implementation in hand-held instruments. |
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format | Article |
id | doaj.art-b76b7da57f414c22be4238b7ad0f5bdc |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-04-11T12:35:54Z |
publishDate | 2019-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Energies |
spelling | doaj.art-b76b7da57f414c22be4238b7ad0f5bdc2022-12-22T04:23:37ZengMDPI AGEnergies1996-10732019-03-0112591410.3390/en12050914en12050914Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded SystemMaría-Ángeles Cifredo-Chacón0Fernando Perez-Peña1Ángel Quirós-Olozábal2Juan-José González-de-la-Rosa3Microelectronic Circuit Design Group, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, SpainApplied Robotics Lab, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, SpainMicroelectronic Circuit Design Group, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, SpainComputational Instrumentation and Industrial Electronics Group, Escuela Politécnica Superior, University of Cádiz, Avda. Ramón Puyol S/N, E-11202 Algeciras-Cádiz, SpainMotivated by the effects of deregulation over power quality and the subsequent need of new types of measurements, this paper assesses different implementations of an estimate for the spectral kurtosis, considered as a low-level harmonic detection. Performance of a processor-based system is compared with a field programmable gate array (FPGA)-based solution, in order to evaluate the accuracy of this processing function for implementation in autonomous measurement equipment. The fourth-order spectrum, with applications in different fields, needs advanced digital signal processing, making it necessary to compare implementation alternatives. In order to obtain reproducible results, the implementations have been developed using common design and programming tools. Several characteristics of the implementations are compared, showing that the increasing complexity and reduced cost of the current FPGA models make the implementation of complex mathematical functions feasible. We show that FPGAs improve the processing capability of the best processor using an operating frequency 33 times lower. This fact strongly supports its implementation in hand-held instruments.http://www.mdpi.com/1996-1073/12/5/914reconfigurable computingFPGApower qualityspectral kurtosisdigital signal processingembedded system |
spellingShingle | María-Ángeles Cifredo-Chacón Fernando Perez-Peña Ángel Quirós-Olozábal Juan-José González-de-la-Rosa Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System Energies reconfigurable computing FPGA power quality spectral kurtosis digital signal processing embedded system |
title | Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System |
title_full | Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System |
title_fullStr | Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System |
title_full_unstemmed | Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System |
title_short | Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System |
title_sort | implementation of processing functions for autonomous power quality measurement equipment a performance evaluation of cpu and fpga based embedded system |
topic | reconfigurable computing FPGA power quality spectral kurtosis digital signal processing embedded system |
url | http://www.mdpi.com/1996-1073/12/5/914 |
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