Exergy optimization of a novel hydrogen production plant with fuel cell, heat recovery, and MED using NSGAII genetic algorithm. (22nd July 2022)

• Record Type: Journal Article
• Authors: Al-Rashed, Abdullah A.A.A.; Alsarraf, Jalal; Alnaqi, Abdulwahab A.
• Is Part Of: International journal of hydrogen energy. Volume 47:Number 62(2022)
• Page Start: 26673
• Page End: 26686
• Publication Date: 2022-07-22
• Subjects: Hydrogen production -- Optimization -- Fuel cell -- Exergy analysis -- Economic assessment; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2021.12.215
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: In the current research, 4E analysis and multi-criteria optimization are applied to the poly generation unit for power, heating, refrigeration, and freshwater generation. This system consists of a solid oxide fuel cell (SOFC), multi-effect thermal vapor desalination (MED-TVC), an organic system with ejector refrigeration (OSER), a heat recovery steam generator (HRSG) and a domestic hot water generator. The mathematical simulation is applied to assess the performance of the plant at design conditions and the genetic algorithm finds the optimum operating point with two different scenarios. Parametric analysis and multi-objective optimization are carried out. Findings represent that the developed plant can provide 257.65 kW power, 12.13 kW, 7.44 kW cooling and heating load, and 0.04 kg/s freshwater with a total cost rate of 10.62 $/h. In this case, the plant energy and exergy efficiency is 73.9% and 71.35% respectively. The results of multi-objective optimization show that these values can be improved to 79% and 73.9% respectively. In addition, the plant cost can be reached to 10.07 $/h in this condition. Highlights: Exergy optimization of a novel hydrogen production plant. SOFC unit can improve the performance of the conventional micro gas turbine cycle. Energy and exergy efficiency improves from 73.9% to 79% and from 71.35% to 73.9%. With optimization the total cost of the plant can be decreased to 9.26 $/h.