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

This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines PythonTM for acquisition and GrafanaTM for results representation. This study aims to benefit communities, by demonstrating how to achieve more efficient energy...

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Published inData (Basel) Vol. 7; no. 6; p. 77
Main Authors Fernández-Morales, Javier, González-de-la Rosa, Juan-José González-de-la, Sierra-Fernández, José-María, Espinosa-Gavira, Manuel-Jesús, Florencias-Oliveros, Olivia, Agüera-Pérez, Agustín, Palomares-Salas, José-Carlos, Remigio-Carmona, Paula
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2022
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Abstract This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines PythonTM for acquisition and GrafanaTM 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.
AbstractList This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines PythonTM for acquisition and GrafanaTM 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.Dataset:https://doi.org/10.7910/DVN/EGI7X1Dataset License: CC0 1.0
This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines PythonTM for acquisition and GrafanaTM 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.
Author Remigio-Carmona, Paula
González-de-la Rosa, Juan-José González-de-la
Florencias-Oliveros, Olivia
Palomares-Salas, José-Carlos
Sierra-Fernández, José-María
Fernández-Morales, Javier
Espinosa-Gavira, Manuel-Jesús
Agüera-Pérez, Agustín
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Cites_doi 10.1109/EPQU.2011.6128842
10.3390/su132111836
10.20944/preprints202110.0260.v1
10.1109/ICHQP.2014.6842886
10.1109/EEEIC.2010.5489989
10.1109/AMPS.2014.6947712
10.1109/PECON.2006.346639
10.1109/PSCC.2014.7038371
10.1109/PEE.2017.8171702
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ContentType Journal Article
Copyright 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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StartPage 77
SubjectTerms Anomalies
Data acquisition
Data analysis
Data base management systems
Datasets
Electric potential
Electrical networks
Energy management
GrafanaTM
grid frequency
higher-order statistics
LabVIEWTM
Maintenance
Monitoring
network-attached storage
Optimization
Power
power quality
Public buildings
Representations
Statistical analysis
Uniqueness
Voltage
Wavelet transforms
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Title Statistical Dataset and Data Acquisition System for Monitoring the Voltage and Frequency of the Electrical Network in an Environment Based on Python and Grafana
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