3E investigation and artificial neural network optimization of a new triple-flash geothermally-powered configuration

• Published in: Renewable Energy
• Main Author: Hai T.; Asadollahzadeh M.; Chauhan B.S.; AlQemlas T.; Elbadawy I.; Salah B.; Feyzbaxsh M.
• Format: Article
• Language: English
• Published: Elsevier Ltd 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164693494&doi=10.1016%2fj.renene.2023.118935&partnerID=40&md5=dbe443982088d4acc51476da9d454cf6

Geothermal systems are among the world's most well-appreciated sources for providing heat to generate power and exploit in numerous ways, attracting attention worldwide due to abundancy and renewability. The present investigation is dedicated to a cogeneration system providing power and hot water for domestic use. The novel system consists of three flash chambers and three turbines intended for power production. The heat source is geothermal subterranean reservoir. Furthermore, thermoelectric generators were creatively implemented as substitutions for condensers so to produce surplus power by utilizing waste heat. The proposed cycle was primarily analyzed with respect to the first and second laws of thermodynamics. As an additional novelty, entransy analysis was also included. After which, the findings were validated in accordance to previously verified scientific resources. The study revealed that the overall power production in the basic mode was 133 kW, 35.62 kW of which was generated by the TEGs. Further, the first and second law efficiencies for the integrated cycle were 26.8% and 64.8, respectively. The sum of entransy loss throughout the integrated system was 8.77MWK. Eventually, an artificial neural network optimization was performed to identify the optimum states of the system, where exergy efficiency and entransy loss were assigned as the objectives. © 2023 Elsevier Ltd