Conceptual design and evaluation of an innovative hydrogen purification process applying diffusion-absorption refrigeration cycle (Exergoeconomic and exergy analyses)

A novel process for hydrogen purification by a diffusion-absorption refrigeration cycle and auxiliary nitrogen refrigeration stream is proposed and exergoeconomically analyzed. The diffusion-absorption refrigeration cycle provides a refrigeration load of 7.125 kW at a refrigeration temperature of −32.61 °C. The coefficient of performance of this refrigeration cycle is calculated to be 0.424. The thermal energy of 16.81 kW is supplied to drive the refrigeration unit. This refrigeration system utilizes ammonia as the refrigerant, water as the absorbent, and helium as the inert gas. The feed gas stream is divided into high-hydrogen and low-hydrogen streams by passing through cryogenic heat exchangers, expansion valves, and flash drums. The inlet unprocessed stream consists of H2, CH4, C2H6, C3H8, N2, and C6H6. Power of 63.42 kW is consumed by the compressors and air coolers to increase the pressure of the feed stream to 4482 kPa. The Aspen HYSYS V11 simulator and MATLAB software are utilized to develop the integrated process and perform the exergy-economic analysis. It was found that the purity of the separated hydrogen stream is about 88%. Two novel criteria for the overall exergy efficiency are introduced to evaluate the overall exergy efficiency of the process. The first and the second-mentioned criteria are computed as 93.825% and 35.053%, respectively. Also, the overall exergy destruction rate is found to be 45.764 kW that 32% of the irreversibility occurred in the air cooler as the main component of exergy wasting. Exergy-economic analysis of the system shows that air coolers are the most important equipment of the plant and should be precisely designed, manufactured, and arranged. Besides, the highest amount of relative cost difference and exergoeconomic factor are related to HX-104 and HX-107 heat exchangers with values of 750.34% and 60.53%, respectively. Finally, sensitivity analyses are conducted to determine the effective parameters on the system performance.