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| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Universidad de Antioquia
2022
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| Online-Zugang: | https://www.redalyc.org/articulo.oa?id=43069426003 https://www.redalyc.org/journal/430/43069426003/ https://www.redalyc.org/journal/430/43069426003/html/ https://www.redalyc.org/journal/430/43069426003/43069426003.epub https://www.redalyc.org/journal/430/43069426003/movil |
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Inhaltsangabe:
- Method of monitoring and detection of failures in PV system based on machine learning Darío Javier Benavides Páúl Arévalo-Cordero Luis G. Gonzalez Luis Hernández-Callejo Francisco Jurado José A. Aguado Ingeniería monitoring Artificial intelligence renewable energy sources Machine learning methods have been used to solve complicated practical problems in different areas and are becoming increasingly popular today. The purpose of this article is to evaluate the prediction of the energy production of three different photovoltaic systems and the supervision of measurement sensors, through Machine learning and data mining in response to the behavior of the climatic variables of the place under study. On the other hand, it also includes the implementation of the resulting models in the SCADA system through indicators, which will allow the operator to actively manage the electricity grid. It also offers a strategy in simulation and prediction in real-time of photovoltaic systems and measurement sensors in the concept of smart grids. 2022 artículo científico 0120-6230 https://www.redalyc.org/articulo.oa?id=43069426003 https://www.redalyc.org/journal/430/43069426003/ https://www.redalyc.org/journal/430/43069426003/html/ https://www.redalyc.org/journal/430/43069426003/43069426003.epub https://www.redalyc.org/journal/430/43069426003/movil 10.17533/udea.redin.20200694 en http://www.redalyc.org/revista.oa?id=430 Revista Facultad de Ingeniería Universidad de Antioquia application/pdf Universidad de Antioquia Revista Facultad de Ingeniería Universidad de Antioquia (Colombia) Num.102