محمد جواد راجي اسدآيادي

In this study, an integrated multiple generation system based on solid oxide fuel cell as the primary driver has been investigated. The current system consists of sub-systems of Kalina power generation cycle, thermoelectric generator, proton exchange membrane electrolyzer, reverse osmosis desalination system and surface absorption chiller. Considering that the solid oxide fuel cell is basically a power generation system, but it has a significant amount of waste heat, the Kalina cycle and surface absorption chiller are used as subsystems that directly use the waste heat of the solid oxide fuel cell. Has been studied. In addition, in order to start the reverse osmosis desalination system and the proton exchange membrane electrolyzer, the total power produced by the Kalina cycle and the thermoelectric generator that replaces the Kalina cycle condenser are used equally. The eva‎luation of the current system has been investigated based on energy, exergy, economic and environmental perspectives. The performance of the system has been investigated in basic conditions and the exergy destruction of the system components and the cost rate of each component have been shown. In order to better understand how the system works, the effect of a number of input parameters on cycle outputs has been eva‎luated. Also, to identify the inputs that show the greatest impact on the main outputs of the system, a sensitivity analysis has been performed. On the other hand, in order to know the most optimal performance conditions of the system, three different cases of optimization have been investigated. In order to reduce the optimization time, a new method based on data science and machine learning has been used. In the first optimization problem, considering the exergy efficiency and the cost rate as the objective functions of the system, the optimal amount of the aforementioned outputs are obtained as 59.92% and 58.03 dollars per hour, respectively. Considering the amount of fresh water produced and the cost rate as objective functions, the above values are obtained at the optimal point, respectively, 1346.30 cubic meters per year and 120.99 dollars per hour. In addition, in the third optimization problem, in which production cooling and cost rate are considered as objective functions, their optimal values are obtained as 272.6 kW and 70.69 dollars per hour, respectively. .

سيستم توليد چندگانه , پيل سوختي اكسيد جامد , بازيابي حرارت اتلافي , چيلر جذب سطحي , آناليز زيست محيطي , يادگيري ماشين

Multi generation system , solid oxide fuel cell , Waste Heat Recovery , Adsorption chiller , Environmental analysis , Machine Learning

Mohammad Javad raji

Dr. Mehdi Moghimi