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Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids

Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical qua...

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Autores principales: Nainar, Karthikeyan, Ciontea, Catalin Iosif, Shahid, Kamal, Iov, Florin, Olsen, Rasmus Løvenstein, Schäler, Christine, Schwefel, Hans-Peter Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433958/
https://www.ncbi.nlm.nih.gov/pubmed/34502661
http://dx.doi.org/10.3390/s21175770
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author Nainar, Karthikeyan
Ciontea, Catalin Iosif
Shahid, Kamal
Iov, Florin
Olsen, Rasmus Løvenstein
Schäler, Christine
Schwefel, Hans-Peter Christian
author_facet Nainar, Karthikeyan
Ciontea, Catalin Iosif
Shahid, Kamal
Iov, Florin
Olsen, Rasmus Løvenstein
Schäler, Christine
Schwefel, Hans-Peter Christian
author_sort Nainar, Karthikeyan
collection PubMed
description Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical quantities such as voltages, currents and power at each customer connection point. Various smart grid applications can make use of the AMI data either in offline or close to real-time mode to assess the grid voltage conditions and estimate losses in the lines/cables. The outputs of these applications can enable DSOs to take corrective action and make a proper plan for grid upgrades. In this paper, the process of development and deployment of applications for improving the observability of distributions grids is described, which consists of the novel deployment framework that encompasses the proposition of data collection, communication to the servers, data storage, and data visualization. This paper discussed the development of two observability applications for grid monitoring and loss calculation, their validation in a laboratory setup, and their field deployment. A representative distribution grid in Denmark is chosen for the study using an OPAL-RT real-time simulator. The results of the experimental studies show that the proposed applications have high accuracy in estimating grid voltage magnitudes and active energy losses. Further, the field deployment of the applications prove that DSOs can gain insightful information about their grids and use them for planning purposes.
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spelling pubmed-84339582021-09-12 Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids Nainar, Karthikeyan Ciontea, Catalin Iosif Shahid, Kamal Iov, Florin Olsen, Rasmus Løvenstein Schäler, Christine Schwefel, Hans-Peter Christian Sensors (Basel) Article Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical quantities such as voltages, currents and power at each customer connection point. Various smart grid applications can make use of the AMI data either in offline or close to real-time mode to assess the grid voltage conditions and estimate losses in the lines/cables. The outputs of these applications can enable DSOs to take corrective action and make a proper plan for grid upgrades. In this paper, the process of development and deployment of applications for improving the observability of distributions grids is described, which consists of the novel deployment framework that encompasses the proposition of data collection, communication to the servers, data storage, and data visualization. This paper discussed the development of two observability applications for grid monitoring and loss calculation, their validation in a laboratory setup, and their field deployment. A representative distribution grid in Denmark is chosen for the study using an OPAL-RT real-time simulator. The results of the experimental studies show that the proposed applications have high accuracy in estimating grid voltage magnitudes and active energy losses. Further, the field deployment of the applications prove that DSOs can gain insightful information about their grids and use them for planning purposes. MDPI 2021-08-27 /pmc/articles/PMC8433958/ /pubmed/34502661 http://dx.doi.org/10.3390/s21175770 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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/).
spellingShingle Article
Nainar, Karthikeyan
Ciontea, Catalin Iosif
Shahid, Kamal
Iov, Florin
Olsen, Rasmus Løvenstein
Schäler, Christine
Schwefel, Hans-Peter Christian
Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title_full Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title_fullStr Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title_full_unstemmed Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title_short Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
title_sort experimental validation and deployment of observability applications for monitoring of low-voltage distribution grids
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433958/
https://www.ncbi.nlm.nih.gov/pubmed/34502661
http://dx.doi.org/10.3390/s21175770
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