May 6, 2024
Shoaib Khanmohammadi

Shoaib Khanmohammadi

Academic rank: Associate professor
Address: Department of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, Iran
Education: Ph.D in Mechanical Engineering
Phone: 0833-8305001
Faculty: Faculty of Engineering

Research

Title
Exergoeconomic assessment and multiobjective optimization of a geothermal-based trigeneration system for electricity, cooling, and clean hydrogen production
Type Article
Keywords
Exergy Cost Bi-objective optimization Hydrogen production
Researchers Farayi Musharavati، Pouria Ahmadi، Shoaib Khanmohammadi

Abstract

Current work deals with exergy and exergoeconomic performance evaluation and bi-objective optimization of a newly introduced advanced energy system with geothermal source. The suggested system is composed of a low-grade organic Rankine cycle, an absorption chiller, and a low-temperature PEM electrolyzer. In three stages, the thermal energy of geo-fluid is transferred to the organic Rankine cycle, the refrigeration cycle, and the PEM electrolyzer. The generated electricity by ORC feeds to the electrolyzer to produce hydrogen as a suitable energy storage. Using a prepared code in MATLAB software, thermodynamic and economic behavior of the system is simulated properly. The exergy analysis outcomes show that the PEM electrolyzer, generator, and heat exchanger are responsible of 77% of total exergy destruction rate of studied system so that electrolyzer with 1218 kW has the highest irreversibility among all components. Calculations show that the overall energy and exergy efficiency of the system are 41 and 50%. In addition, parametric study on different variables such as geothermal source temperature, reference environment temperature, and turbine inlet pressure is considered. To find the optimum states of studied system, various bi-objective scenarios are presented. The results of optimization represent that based on introduced optimization states and employing designer criteria, the best optimum state of suggested system can be determined. A novel aspect of current works goes back to the bi-criteria optimization to determine the optimum states of the suggested system.