Methodology for the Surveillance the Voltage Supply in Public Buildings Using the ITIC Curve and Python Programming

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 and José-Carlos Palomares-Salas
Additional contact information
Javier Fernández-Morales: Research Group PAIDI-TIC-168, Department of Automation Engineering, Electronics, Architecture and Computers Networks, Higher Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, 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 Technical School of Engineering, University of Cádiz, E-11202 Algeciras, Spain

Data, 2022, vol. 7, issue 11, 1-10

Abstract: This paper proposes an easy-to-implement method for detecting and assessing two of the most frequent PQ (Power Quality) problems: voltage sags and swells. These can affect sensitive equipment such as computers, programmable logic controllers, contactors, etc. Therefore, it is of great interest to implement it in any laboratory, not only for protection reasons but also as a safeguard for claims against the supply company. Thanks to the actual context, in which it is possible to manage big volumes of data, connect multiple devices with IoT (Internet of Things), etc., it is feasible and of great interest to monitor the voltage at specific points of the network. This makes it possible to detect voltage sags and swells and diagnose which points are more prone to this type of problems. For the detection of sags and swells, a program written in Python is in charge of crawling all the files in the database and target those RMS values that fall outside the established limits. Compared to LabVIEW, which might have been the most logical alternative, being the acquisition hardware from the same company (National Instruments), Python has a higher computational performance and is also free of charge, unlike LabVIEW. Thanks to the libraries available in Python , it allows a hardware control close to what is possible using LabVIEW. Implemented in MATLAB, the ITIC (Information Technology Industry Council) power acceptability curve reflects the impact of these power quality disturbances in electrical power systems. The results showed that the combined action of Python and MATLAB performed well on a conventional desktop computer.

Keywords: observational data analysis; voltage sag; voltage swell; power quality; quality indices; higher-order statistics; ITIC; acceptance curves; Python (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2306-5729/7/11/162/pdf (application/pdf)
https://www.mdpi.com/2306-5729/7/11/162/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jdataj:v:7:y:2022:i:11:p:162-:d:975256

Access Statistics for this article

Data is currently edited by Ms. Cecilia Yang

More articles in Data from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().