Intelligence-driven power quality monitoring
Power quality is an issue that needs continual attention and have increasingly been used as the key indicator for benchmarking of the true performance of many utilities in the world. Since quality of voltage holds significant importance in the functionality of any power network, monitoring of voltag...
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my.uniten.dspace-298892023-12-28T16:58:04Z Intelligence-driven power quality monitoring Hakimie H. Ramachandaramurthy V.K. Mukerjee R.N. 16021651800 6602912020 7003827066 Fault location Monitoring system Benchmarking Computer simulation Electric fault location Electric power distribution Electric power generation Electric power transmission Intelligent agents Monitoring systems Power quality Power systems Electric power systems Power quality is an issue that needs continual attention and have increasingly been used as the key indicator for benchmarking of the true performance of many utilities in the world. Since quality of voltage holds significant importance in the functionality of any power network, monitoring of voltage quality has become a major area of investigation. The extreme financial burden required may not be favourable to provide measurements at each bus and line in a network in both transmission and distribution levels. However, to decide on the remedial measures, it is imperative to identify the type and the location of the fault in a power system. In this paper, an overview of the intelligence-driven power quality monitoring system is described. The intelligence-driven monitoring system is used to enhance system observability through pseudo-measurement data generation. Investigation and simulation were performed on a regional network. Subsequently, the type of fault and the probable location of fault whether it is in transmission or distribution level leading to the degradation of quality were identified. � 2005 IEEE. Final 2023-12-28T08:58:04Z 2023-12-28T08:58:04Z 2005 Conference paper 2-s2.0-33847256489 https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847256489&partnerID=40&md5=12ea49f88ebb16303c9a2e0c5d1da257 https://irepository.uniten.edu.my/handle/123456789/29889 2 1619884 1278 1282 Scopus |
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Fault location Monitoring system Benchmarking Computer simulation Electric fault location Electric power distribution Electric power generation Electric power transmission Intelligent agents Monitoring systems Power quality Power systems Electric power systems |
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Fault location Monitoring system Benchmarking Computer simulation Electric fault location Electric power distribution Electric power generation Electric power transmission Intelligent agents Monitoring systems Power quality Power systems Electric power systems Hakimie H. Ramachandaramurthy V.K. Mukerjee R.N. Intelligence-driven power quality monitoring |
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Power quality is an issue that needs continual attention and have increasingly been used as the key indicator for benchmarking of the true performance of many utilities in the world. Since quality of voltage holds significant importance in the functionality of any power network, monitoring of voltage quality has become a major area of investigation. The extreme financial burden required may not be favourable to provide measurements at each bus and line in a network in both transmission and distribution levels. However, to decide on the remedial measures, it is imperative to identify the type and the location of the fault in a power system. In this paper, an overview of the intelligence-driven power quality monitoring system is described. The intelligence-driven monitoring system is used to enhance system observability through pseudo-measurement data generation. Investigation and simulation were performed on a regional network. Subsequently, the type of fault and the probable location of fault whether it is in transmission or distribution level leading to the degradation of quality were identified. � 2005 IEEE. |
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16021651800 |
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16021651800 Hakimie H. Ramachandaramurthy V.K. Mukerjee R.N. |
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Conference paper |
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Hakimie H. Ramachandaramurthy V.K. Mukerjee R.N. |
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Hakimie H. |
title |
Intelligence-driven power quality monitoring |
title_short |
Intelligence-driven power quality monitoring |
title_full |
Intelligence-driven power quality monitoring |
title_fullStr |
Intelligence-driven power quality monitoring |
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Intelligence-driven power quality monitoring |
title_sort |
intelligence-driven power quality monitoring |
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2023 |
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1806428137241706496 |
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13.222552 |