Exploración en el dimensionamiento de sistemas de energía solar térmica para acs usando redes neuronales artificiales
保存先:
| 著者: | , |
|---|---|
| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2021 |
| その他の書誌記述: | Thermal systems that include the use of solar collectors are used for heating water with solar energy. The most common collector for this type of application is the flat plate collector. The thermal system design process involves, among other aspects, the dimensioning of the collector surface area, which is determined from environmental conditions, available solar energy conditions, geographical location, collector placement conditions, the water demand, and manufacturing characteristics of the collector; as well as design protocols that are standardized. In the present work the use of artificial neural networks as a technological tool in the dimensioning of the collecting area is explored. To evaluate the reliability of the estimation, the linear correlation factor R was used as a performance indicator. The results show that the estimation using the elaborated technique is reliable and can be used in a generalized way. |
| 国: | Portal de Revistas UCR |
| 機関: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| 言語: | Español |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/45600 |
| オンライン･アクセス: | https://archivo.revistas.ucr.ac.cr/index.php/cienciaytecnologia/article/view/45600 |