Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs

This study offers an in-depth thermodynamic analysis and optimization of an integrated renewable energy system that merges a double-flash geothermal system with a transcritical carbon dioxide Rankine cycle, utilizing machine learning algorithms. The innovative design aims to maximize the concurrent...

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Bibliographic Details
Main Authors:	Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan
Format:	Article
Language:	English
Published:	Elsevier 2024-11-01
Series:	Case Studies in Thermal Engineering
Subjects:	Geothermal energy Integrated renewable system Artificial intelligence Machine learning Optimization
Online Access:	http://www.sciencedirect.com/science/article/pii/S2214157X24012413
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs

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