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Reconfiguration of photovoltaic panels for reducing the hydrogen consumption in fuel cells of hybrid systems

Reconfiguración de paneles fotovoltaicos para reducción del consumo de hidrógeno en las celdas de combustible de sistemas híbridos

dc.creatorGonzález-Montoya, Daniel
dc.creatorRamos-Paja, Carlos A.
dc.creatorBolaños-Martínez, Freddy
dc.creatorRamírez-Quiroz, Fabio
dc.creatorCamarillo-Peñaranda, Juan R.
dc.creatorTrejos-Grisales, Adriana
dc.date2017-05-02
dc.date.accessioned2021-03-18T21:06:45Z
dc.date.available2021-03-18T21:06:45Z
dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/692
dc.identifier10.22430/22565337.692
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/11691
dc.descriptionHybrid generation combines advantages from fuel cell systems with non-predictable generation approaches, such as photovoltaic and wind generators. In such hybrid systems, it is desirable to minimize as much as possible the fuel consumption, for the sake of reducing costs and increasing the system autonomy. This paper proposes an optimization algorithm, referred to as population-based incremental learning, in order to maximize the produced power of a photovoltaic generator. This maximization reduces the fuel consumption in the hybrid aggregation. Moreover, the algorithm's speed enables the real-time computation of the best configuration for the photovoltaic system, which also optimizes the fuel consumption in the complementary fuel cell system. Finally, a system experimental validation is presented considering 6 photovoltaic modules and a NEXA 1.2KW fuel cell. Such a validation demonstrates the effectiveness of the proposed algorithm to reduce the hydrogen consumption in these hybrid systems.en-US
dc.descriptionLa generación eléctrica híbrida combina las ventajas de las celdas de combustible con sistemas de generación difíciles de predecir, como los fotovoltaicos y eólicos. El principal objetivo en este tipo de sistemas híbridos es minimizar el consumo de hidrógeno reduciendo costos e incrementando la autonomía del sistema. Este articulo propone un algoritmo de optimización, conocido como algoritmo de aprendizaje incremental basado en población, el cual tienen como objetivo maximizar la potencia producida por un generador fotovoltaico. Esta maximización reduce el consumo de hidrógeno combustible del sistema basado en hidrógeno. Adicionalmente, la velocidad de convergencia del algoritmo permite la computación en tiempo real de la mejor configuración para el sistema fotovoltaico, permitiendo una optimización dinámica del consumo de hidrógeno de la celda de combustible. Finalmente, se presenta una validación experimental del sistema considerando 6 paneles fotovoltaicos y una celda de combustible NEXA de 1.2 KW. Esta validación, demuestra la efectividad del algoritmo propuesto para la reducción del consumo de hidrógeno en este tipo de sistemas híbridos.es-ES
dc.formatapplication/pdf
dc.languagespa
dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/692/674
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dc.rightshttps://creativecommons.org/licenses/by/3.0/deed.es_ESen-US
dc.sourceTecnoLógicas; Vol. 20 No. 39 (2017); 83-97en-US
dc.sourceTecnoLógicas; Vol. 20 Núm. 39 (2017); 83-97es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectfuel cellen-US
dc.subjectreconfiguration of photovoltaic systemsen-US
dc.subjecthybrid generationen-US
dc.subjectpopulationbased incremental learningen-US
dc.subjectCelda de combustiblees-ES
dc.subjectreconfiguración sistemas fotovoltaicoses-ES
dc.subjectgeneración híbridaes-ES
dc.subjectaprendizaje incremental basado en poblaciónes-ES
dc.titleReconfiguration of photovoltaic panels for reducing the hydrogen consumption in fuel cells of hybrid systemsen-US
dc.titleReconfiguración de paneles fotovoltaicos para reducción del consumo de hidrógeno en las celdas de combustible de sistemas híbridoses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES


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