May 24, 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


Proposal of a new low-temperature thermodynamic cycle: 3E analysis and optimization of a solar pond integrated with fuel cell and thermoelectric generator
Type Article
Salinity gradient solar pond, PEM fuel Cell, Waste heat recovery, TOPSIS
Researchers Farayi Musharavati، Shoaib Khanmohammadi، Joy Nondy، Tapan Gogoi


The present research deals with a novel hybrid system that comprises of a salinity gradient solar pond (SGSP) integrated with a proton exchange membrane fuel cell (PEMFC) and a thermoelectric generator (TEG). The key novelty of this research is the use of PEMFC waste heat to increase the performance of the low-temperature heat source (solar pond). Also, a thermoelectric generator is employed in the proposed setup for complete waste energy recovery. In this paper, the proposed system's energy, exergy, and economic (3E) performance are investigated, as well as compared with two additional systems that were modelled by excluding TEG and PEMFC to showcase the benefits of the sub-systems in the final configuration. A parametric study is also conducted to investigate the effect of significant parameters on the overall system performance. The simulation results indicated that the integrated system's net output power is 2288.8 kW at a base case operating condition, with energy and exergy efficiency of 11.26% and 13.17%, respectively, and a system cost rate of 394 $/h. In comparison to other components in the integrated system, SGSP alone accounts for 75% of total exergy degradation and has the highest investment cost rate of 66.70 $/h. Further, to achieve the best system performance, a multi-criteria optimization is performed for the suggested system with net output power, energy efficiency, exergy efficiency, and system cost rate as objective functions. Besides, the multi-criteria decision analysis (MCDA) is also carried out on the obtained Pareto front using TOPSIS decision-maker to select the best operating condition that improves the output power, energy, and exergy efficiency by 52.6%, 49.6%, and 61.8%, respectively, at the expense of 5.2% increase in the system cost rate. The current investigation demonstrates how an appropriate optimized design of an integrated energy system using SGSP, PEMFC, and TEG can improve the overall performance with reasonable cost increment