Performance analysis and neural modelling of a greenhouse integrated photovoltaic system
In the modern agriculture, greenhouses are well established as technological solutions aimed to increase plants productivity and crops quality. Greenhouses can include added capabilities for the energy generation by the integration of photovoltaic solar modules in their cladding areas provided that...
| Main Authors: | , , , |
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| 格式: | info:eu-repo/semantics/article |
| 语言: | English |
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2023
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| 主题: | |
| 在线阅读: | http://hdl.handle.net/10835/14819 |
| _version_ | 1789406359739957248 |
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| author | Pérez Alonso, José Pérez García, Manuel Pasamontes Romera, M Callejón Ferre, Ángel Jesús |
| author_facet | Pérez Alonso, José Pérez García, Manuel Pasamontes Romera, M Callejón Ferre, Ángel Jesús |
| author_sort | Pérez Alonso, José |
| collection | DSpace |
| description | In the modern agriculture, greenhouses are well established as technological solutions aimed to increase plants productivity and crops quality. Greenhouses can include added capabilities for the energy generation by the integration of photovoltaic solar modules in their cladding areas provided that the blocking effect of photosynthetically active radiation is not significant for plants growing. After a comprehensive literature survey on the integration of photovoltaic systems in greenhouses, this work describes the results of an experience carried out at Almería (South Eastern Spain), where it has been built and monitored a 1.024 m2 pilot photovoltaic greenhouse. The experimental set up has consisted of a greenhouse roof 9.79% coverage ratio by means of 24 flexible thin film modules, installed in two different checkerboard configurations. The obtained results indicate that, for the conditions of the undertaken experiment, the yearly electricity production normalised to the greenhouse ground surface is 8.25 kW h m−2, concordant to previous findings for the used type of modules. In addition to this, an artificial neural network model has been elaborated to predict the electricity instantaneous production of the system, showing the suitability of this modelling technique for complex and non linear systems, as it is the case of the constructively integrated PV plants, either in greenhouses and buildings, where both impinging radiation and system configuration are highly constrained by the pre-existing structures. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14819 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2023 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-148192023-12-15T12:50:56Z Performance analysis and neural modelling of a greenhouse integrated photovoltaic system Pérez Alonso, José Pérez García, Manuel Pasamontes Romera, M Callejón Ferre, Ángel Jesús Greenhouse Thin film modules Artificial neural network In the modern agriculture, greenhouses are well established as technological solutions aimed to increase plants productivity and crops quality. Greenhouses can include added capabilities for the energy generation by the integration of photovoltaic solar modules in their cladding areas provided that the blocking effect of photosynthetically active radiation is not significant for plants growing. After a comprehensive literature survey on the integration of photovoltaic systems in greenhouses, this work describes the results of an experience carried out at Almería (South Eastern Spain), where it has been built and monitored a 1.024 m2 pilot photovoltaic greenhouse. The experimental set up has consisted of a greenhouse roof 9.79% coverage ratio by means of 24 flexible thin film modules, installed in two different checkerboard configurations. The obtained results indicate that, for the conditions of the undertaken experiment, the yearly electricity production normalised to the greenhouse ground surface is 8.25 kW h m−2, concordant to previous findings for the used type of modules. In addition to this, an artificial neural network model has been elaborated to predict the electricity instantaneous production of the system, showing the suitability of this modelling technique for complex and non linear systems, as it is the case of the constructively integrated PV plants, either in greenhouses and buildings, where both impinging radiation and system configuration are highly constrained by the pre-existing structures. 2023-12-15T12:50:55Z 2023-12-15T12:50:55Z 2012-06-27 info:eu-repo/semantics/article 13640321 http://hdl.handle.net/10835/14819 en https://doi.org/10.1016/j.rser.2012.04.002 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Greenhouse Thin film modules Artificial neural network Pérez Alonso, José Pérez García, Manuel Pasamontes Romera, M Callejón Ferre, Ángel Jesús Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title | Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title_full | Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title_fullStr | Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title_full_unstemmed | Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title_short | Performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| title_sort | performance analysis and neural modelling of a greenhouse integrated photovoltaic system |
| topic | Greenhouse Thin film modules Artificial neural network |
| url | http://hdl.handle.net/10835/14819 |
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