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Statistical Dataset and Data Acquisition System for Monitoring the Voltage and Frequency of the Electrical Network in an Environment Based on Python and Grafana

Author

Listed:
  • Javier Fernández-Morales

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • Juan-José González-de-la Rosa

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • José-María Sierra-Fernández

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • Manuel-Jesús Espinosa-Gavira

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • Olivia Florencias-Oliveros

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • Agustín Agüera-Pérez

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • José-Carlos Palomares-Salas

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

  • Paula Remigio-Carmona

    (Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher-Polytechnic School of Algeciras, University of Cádiz, E-11202 Algeciras, Spain)

Abstract

This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines Python TM for acquisition and Grafana TM for results representation. This study aims to benefit communities, by demonstrating how to achieve more efficient energy management. The study outlines how to obtain a more realistic vision of the quality of the supply, that is oriented to the monitoring of the state of the network; this should allow for better understanding, which should in turn enable the optimization of the operation and maintenance of power systems. Our work focused on frequency and higher order statistical estimators which, combined with exploratory data analysis techniques, improved the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination of low-cost measurement solutions, which have the underlying benefit of contributing to industrial benchmarking. Our study proposes an effective and versatile system, which can do acquisition, statistical analysis, database management and results representation in less than a second. The system offers a wide variety of graphs to present the results of the analysis, so that the user can observe them and identify, with relative ease, any anomalies in the supply which could damage the sensitive equipment of the correspondent installation. It is a system, therefore, that not only provides information about the power quality, but also significantly contributes to the safety and maintenance of the installation. This system can be practically realized, subject to the availability of internet access.

Suggested Citation

  • Javier Fernández-Morales & Juan-José González-de-la Rosa & José-María Sierra-Fernández & Manuel-Jesús Espinosa-Gavira & Olivia Florencias-Oliveros & Agustín Agüera-Pérez & José-Carlos Palomares-Salas , 2022. "Statistical Dataset and Data Acquisition System for Monitoring the Voltage and Frequency of the Electrical Network in an Environment Based on Python and Grafana," Data, MDPI, vol. 7(6), pages 1-10, June.
    • Handle: RePEc:gam:jdataj:v:7:y:2022:i:6:p:77-:d:832752
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    References listed on IDEAS

    as
    1. Jose-María Sierra-Fernández & Olivia Florencias-Oliveros & Manuel-Jesús Espinosa-Gavira & Juan-José González-de-la-Rosa & Agustín Agüera-Pérez & José-Carlos Palomares-Salas, 2021. "Online System for Power Quality Operational Data Management in Frequency Monitoring Using Python and Grafana," Energies, MDPI, vol. 14(24), pages 1-15, December.
    2. Khalid Alnowibet & Andres Annuk & Udaya Dampage & Mohamed A. Mohamed, 2021. "Effective Energy Management via False Data Detection Scheme for the Interconnected Smart Energy Hub–Microgrid System under Stochastic Framework," Sustainability, MDPI, vol. 13(21), pages 1-32, October.
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    Cited by:

    1. Jesús Álvarez-Higueruela & Francisco-José Gutiérrez-Villalba & José-María Sierra-Fernández & Juan-José González-de-la-Rosa & Olivia Florencias-Oliveros & José-Carlos Palomares-Salas & Agustín Agüera-P, 2023. "Characterization of the Hydropower Inlet Effect on the Electric Network Frequency," Energies, MDPI, vol. 16(9), pages 1-13, April.
    2. Javier Fernández-Morales & Juan-José González-de-la-Rosa & José-María Sierra-Fernández & Olivia Florencias-Oliveros & Paula Remigio-Carmona & Manuel-Jesús Espinosa-Gavira & Agustín Agüera-Pérez & José, 2022. "Methodology for the Surveillance the Voltage Supply in Public Buildings Using the ITIC Curve and Python Programming," Data, MDPI, vol. 7(11), pages 1-10, November.

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