Design, evaluation, and optimization of an integrated proton exchange membrane and double flash geothermal based organic Rankine cycle multi-generation system fed by a biomass-fueled gasifier

• Published in: Sustainable cities and society 2024-02, Vol.101, p.105126, Article 105126
• Main Authors: Taheri, Muhammad Hadi, Seker, Utku, Akkurt, Gulden Gokcen, Mohammadpourfard, Mousa
• Format: Article
• Language: English
• Subjects: Biomass energy; Double flash geothermal; Genetic algorithm; Multi-generation; Multi-objective analysis
• ISSN: 2210-6707; 2210-6715
• DOI: 10.1016/j.scs.2023.105126

•A novel geothermal system using a genetic algorithm based optimization is designed.•Using PEM and regenerative ORC with IHE, most of wasted energy is used.•Optimal points: exergy efficiency of 29.8 % and total product cost rate of 6 M$/year.•The combustion chamber and gasifier exhibit the highest exergy destruction. This study introduces an innovative approach by formulating and evaluating a synergistic biomass-geothermal structure, emphasizing optimized inter-component connections. The research stands out for its thorough analysis of parameter impacts on the system and variables, addressing an unexplored aspect in integrated energy systems. The multi-generation systems are the integration of a combined gasification gas turbine cycle, double flash geothermal cycle, and proton exchange membrane cycle for the generating power and hydrogen. The overall system and its subsystems are studied to explore how the performance of thermodynamics and the total cost rate are influenced by operating parameters. The best operational conditions for both subsystems and the overall system have been determined by analyzing the impact of operating parameters on the thermodynamic behavior and environmental impact through parametric studies. The findings indicate while Sabalan's current efficiency is 16.26 %, the system energy efficiency reached 24.89 % when coupled with other renewable source. To enhance the system's efficiency, a genetics algorithm was utilized to simultaneously optimize the total cost of exergy destruction and investment cost. The outcome of the multi-objective optimization revealed that the exergy efficiency of optimal point for the system is 29.8 % and a total investment cost is 6 (M$/year).