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Application of machine learning techniques for asset management and proactive analysis in power systems

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Date
2022-09-12
Author
Rajora, GopaL Lal
Calvo Báscones, Pablo
Mateo Domingo, Carlos
Sanz Bobi, Miguel Ángel
Palacios Hielscher, Rafael
Bolfek, Martin
Vrbicic Tendera, Dajana
Keko, Hrvoje
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info:eu-repo/semantics/publishedVersion
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Abstract
 
 
Today, the generation, transmission, and distribution business of power systems are suffering essential and fast changes in their operative and management strategies worldwide. Some decades ago, the liberalization of the electricity markets introduced a new significant competition factor within the sector, followed by increasing demand for quality of service from customers and public administrations. More recently, the digitalization of power systems and new concepts about Smart Grids allow the collection of more and more information about the power system components. This enables recording data in a more orderly and reliable way that can be used for better operation and maintenance and, ultimately, better management of the available resources in power systems, the main idea of the Asset Management concept.
 
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http://hdl.handle.net/11531/87549
Application of machine learning techniques for asset management and proactive analysis in power systems
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Instituto de Investigación Tecnológica (IIT)
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Condition Monitoring, Intelligent Systems, Assets Management, Proactive Analytics, Power Grids.
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