IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i5p914-d212414.html
   My bibliography  Save this article

Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System

Author

Listed:
  • María-Ángeles Cifredo-Chacón

    (Microelectronic Circuit Design Group, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, Spain)

  • Fernando Perez-Peña

    (Applied Robotics Lab, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, Spain)

  • Ángel Quirós-Olozábal

    (Microelectronic Circuit Design Group, Escuela Superior de Ingeniería, University of Cádiz, Avda. de la Universidad 10, E-11519 Puerto Real-Cádiz, Spain)

  • Juan-José González-de-la-Rosa

    (Computational Instrumentation and Industrial Electronics Group, Escuela Politécnica Superior, University of Cádiz, Avda. Ramón Puyol S/N, E-11202 Algeciras-Cádiz, Spain)

Abstract

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.

Suggested Citation

  • María-Ángeles Cifredo-Chacón & Fernando Perez-Peña & Ángel Quirós-Olozábal & Juan-José González-de-la-Rosa, 2019. "Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System," Energies, MDPI, vol. 12(5), pages 1-15, March.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:914-:d:212414
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/5/914/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/5/914/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Juan José González De la Rosa & José María Sierra-Fernández & José Carlos Palomares-Salas & Agustín Agüera-Pérez & Álvaro Jiménez Montero, 2015. "An Application of Spectral Kurtosis to Separate Hybrid Power Quality Events," Energies, MDPI, vol. 8(9), pages 1-17, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jose-María Sierra-Fernández & Sarah Rönnberg & Juan-José González de la Rosa & Math H. J. Bollen & José-Carlos Palomares-Salas, 2019. "Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics," Energies, MDPI, vol. 12(1), pages 1-15, January.
    2. Alexandre Serrano-Fontova & Pablo Casals Torrens & Ricard Bosch, 2019. "Power Quality Disturbances Assessment during Unintentional Islanding Scenarios. A Contribution to Voltage Sag Studies," Energies, MDPI, vol. 12(16), pages 1-21, August.
    3. José-María Guerrero-Rodríguez & Clemente Cobos-Sánchez & Juan-José González-de-la-Rosa & Diego Sales-Lérida, 2019. "An Embedded Sensor Node for the Surveillance of Power Quality," Energies, MDPI, vol. 12(8), pages 1-20, April.
    4. Misael Lopez-Ramirez & Luis Ledesma-Carrillo & Eduardo Cabal-Yepez & Carlos Rodriguez-Donate & Homero Miranda-Vidales & Arturo Garcia-Perez, 2016. "EMD-Based Feature Extraction for Power Quality Disturbance Classification Using Moments," Energies, MDPI, vol. 9(7), pages 1-15, July.
    5. Juan-José González-de-la-Rosa & Agustín Agüera-Pérez & José-Carlos Palomares-Salas & Olivia Florencias-Oliveros & José-María Sierra-Fernández, 2018. "A Dual Monitoring Technique to Detect Power Quality Transients Based on the Fourth-Order Spectrogram," Energies, MDPI, vol. 11(3), pages 1-12, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:914-:d:212414. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.