Resumen:
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[EN] Renewable energy-based power generation technologies are becoming more and more popular since they represent alternative solutions to the recent economic and environmental problems that modern society is facing. In ...[+]
[EN] Renewable energy-based power generation technologies are becoming more and more popular since they represent alternative solutions to the recent economic and environmental problems that modern society is facing. In this sense, the most widely spread applications for renewable energy generation are the solar photovoltaic and wind generation. Once installed, typically outside, the wind generators and photovoltaic panels suffer the environmental effects due to the weather conditions in the geographical location where they are placed. This situation, along with the normal operation of the systems, cause failures in their components, and on some occasions such problems could be difficult to identify and hence to fix. Thus, there are generated energy production stops bringing as consequence economical losses for investors. Therefore, it is important to develop strategies, schemes, and techniques that allow to perform a proper identification of faults in systems that introduce renewable generation, keeping energy production. In this work, an analysis of the most common faults that appear in wind and photovoltaic generation systems is presented. Moreover, the main techniques and strategies developed for the identification of such faults are discussed in order to address the advantages, drawbacks, and trends in the field of detection and classification of specific and combined faults. Due to the role played by wind and photovoltaic generation, this work aims to serve as a guide to properly select a monitoring strategy for a more reliable and efficient power grid. Additionally, this work will propose some prospective with views toward the existing areas of opportunity, e.g., system improvements, lacks in the fault detection, and tendency techniques that could be useful in solving them.
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Agradecimientos:
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This research was partially funded by Investigación Vinculada a la Atención de Problemas Nacionales 2021 FIN202108 project, and by the Spanish Ministerio de Ciencia Innovación y Universidades; and by FEDER programa un ...[+]
This research was partially funded by Investigación Vinculada a la Atención de Problemas Nacionales 2021 FIN202108 project, and by the Spanish Ministerio de Ciencia Innovación y Universidades; and by FEDER programa un they framework of the Proyectos de I+D de Generación de
Conocimiento del Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y
Tecnológico del Sistema de I+D, Subprograma Estatal de Generación de Conocimiento; (ref: PGC2018‐095747‐B‐I00)
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