Monitoring versus prediction of the power of three different PV technologies in the coast of Lima-Peru
Descripción del Articulo
This article presents the benefits of two simple analytical models for estimating the outdoor performance of three different photovoltaic technologies in Lima, Peru. The Osterwald and the constant fill factor models are implemented to estimate the maximum power delivered by three photovoltaic module...
| Autores: | , , , , , , |
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| Formato: | artículo |
| Fecha de Publicación: | 2021 |
| Institución: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/2367 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/2367 https://doi.org/10.1088/1742-6596/1841/1/012001 |
| Nivel de acceso: | acceso abierto |
| Materia: | Thin films Forecasting Heterojunctions Photovoltaic cells Solar energy Thin film solar cells http://purl.org/pe-repo/ocde/ford#2.02.03 |
| Sumario: | This article presents the benefits of two simple analytical models for estimating the outdoor performance of three different photovoltaic technologies in Lima, Peru. The Osterwald and the constant fill factor models are implemented to estimate the maximum power delivered by three photovoltaic module technologies: aluminum back surface field, heterojunction with intrinsic thin-layer and amorphous/microcrystalline thin-film tandem. A 12-months experimental campaign is carried out through measurements of current-voltage curves, irradiance and module temperature. The results show that both models overestimate the modelled power when compared to the measured one. In order to correct the maximum power predicted by both models, a correction factor is introduced. This correction factor allows us to estimate losses and a respective effective nominal power to minimize the prediction error on a monthly and yearly basis. These parameters demonstrate a unique behavior for each technology during different months implying different seasonal impacts of the ambient variables on the module performance. The effectiveness of this correction factor is demonstrated through accuracy measures. It enables the photovoltaic power prediction with an error < 1% for the particular climate in Lima, Peru. © 2021 Published under licence by IOP Publishing Ltd. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).