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Development and Neural Network Optimization of a Renewable-based System for Hydrogen Production and Desalination by Adel Balali; Mohammad Javad Raji Asadabadi; Javad Rezazadeh Mehrenjani; Ayat Gharehghani; Mahdi Moghimi is a Engineering article available to read on EtoBox.
What is Development and Neural Network Optimization of a Renewable-based System for Hydrogen Production and Desalination about?
This study introduces an integrated system based on geothermal and solar energy to provide useful products such as electricity, freshwater, and hydrogen. In the proposed system, a solar unit including parabolic trough collectors has been used to improve the performance of the system and increase the mentioned products. The lowtemperature geothermal stream returns to the ground after passing through a thermoelectric generator unit. A combination of Rankine and organic Rankine cycles is used to supply electricity and run the water electrolysis unit. This study aims to address the inefficient heat recovery in a combined solar and geothermal resource system by utilizing waste heat to generate clean hydrogen. A parametric study and sensitivity analysis are considered to investigate the effect of design parameters on the main outputs of the system. After evaluating the system from energy, exergy, and economic perspectives, a multi-objective optimization process with a combination of artificial neural network and genetic algorithm was performed on the system. The optimization problem is divided into two cases (scenarios). Each case considers energy efficiency and total cost rate as object
Who reads Development and Neural Network Optimization of a Renewable-based System for Hydrogen Production and Desalination?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Adel Balali; Mohammad Javad Raji Asadabadi; Javad Rezazadeh Mehrenjani; Ayat Gharehghani; Mahdi Moghimi
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Engineering (Physical Sciences)