Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT
Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/21/8206 |
| _version_ | 1797468395940085760 |
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| author | Geno Peter Albert Alexander Stonier Punit Gupta Daniel Gavilanes Manuel Masias Vergara Jong Lung sin |
| author_facet | Geno Peter Albert Alexander Stonier Punit Gupta Daniel Gavilanes Manuel Masias Vergara Jong Lung sin |
| author_sort | Geno Peter |
| collection | DOAJ |
| description | Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly. |
| first_indexed | 2024-03-09T19:06:51Z |
| format | Article |
| id | doaj.art-d680959bf95e4a27b0f246e4b9e63f7f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T19:06:51Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-d680959bf95e4a27b0f246e4b9e63f7f2023-11-24T04:33:40ZengMDPI AGEnergies1996-10732022-11-011521820610.3390/en15218206Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoTGeno Peter0Albert Alexander Stonier1Punit Gupta2Daniel Gavilanes3Manuel Masias Vergara4Jong Lung sin5CRISD, School of Engineering and Technology, University of Technology Sarawak, No.1 Jalan Universiti, Sibu 96000, MalaysiaSchool of Electrical Engineering (SELECT), Vellore Institute of Technology, Vellore 632014, Tamil Nadu, IndiaSchool of computer Science, University College Dublin, D04 V1W8 Dublin, IrelandCenter for Nutrition & Health, Universidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, SpainCenter for Nutrition & Health, Universidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, SpainSarawak Electricity Supply Corporation, Kuching 93050, MalaysiaConventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly.https://www.mdpi.com/1996-1073/15/21/8206fault monitoringnormalizing technologiesMicrosoft Azure Internet of Things (IoT)System Average Interruption Duration IndexSystem Average Interruption Frequency Index |
| spellingShingle | Geno Peter Albert Alexander Stonier Punit Gupta Daniel Gavilanes Manuel Masias Vergara Jong Lung sin Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT Energies fault monitoring normalizing technologies Microsoft Azure Internet of Things (IoT) System Average Interruption Duration Index System Average Interruption Frequency Index |
| title | Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT |
| title_full | Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT |
| title_fullStr | Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT |
| title_full_unstemmed | Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT |
| title_short | Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT |
| title_sort | smart fault monitoring and normalizing of a power distribution system using iot |
| topic | fault monitoring normalizing technologies Microsoft Azure Internet of Things (IoT) System Average Interruption Duration Index System Average Interruption Frequency Index |
| url | https://www.mdpi.com/1996-1073/15/21/8206 |
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