چكيده به لاتين
The multigeneration system proposed in this study is designed to supply needs such as electricity, cooling load, hydrogen, and freshwater for domestic and commercial sectors. Syngas produced through municipal solid waste gasification are used as input fuel to the solid oxide fuel cell (SOFC). The SOFC exhaust gases enter an afterburner to burn completely and then enter a gas turbine for additional power generation. Cascaded ORC is also used to recover waste heat from gas turbine. Liquefied natural gas (LNG) flow is used as a heat sink in ORC to supply the cooling load for domestic use. The simulation of the proposed system has been implemented in MATLAB software, and the performance evaluation of the system has been investigated from the perspective of energy, exergy, economy, and environment. In a parametric study, the effect of the design parameters on the outputs and performance parameters of the system has been discussed. Also, sensitivity analysis has been used to identify the design parameters that have a significant impact on system outputs. The simulation results of the basic system show that the proposed system can produce 714.27 kW of electricity, 323.61 kW of cooling load, 129.45 kg/h of water, and 1.82 kg/h of hydrogen. Also, exergy efficiency, cost rate, and CO2 emission index of the whole system are 39.18%, 32.24 $/h, and 0.102 ton/GJ, respectively. Finally, a novel optimization method based on data science and machine learning has been applied, in which an artificial neural network is integrated with a genetic algorithm. Using this method, the runtime and computational cost were significantly reduced. The optimization results show that in scenario A, considering exergy efficiency and total cost rate as objective functions, the optimal values are 44.77% and 30.53 $/h, respectively. In scenario B, when the objective functions are exergy efficiency and CO2 emission index, the optimal values reach 43.04% and 0.1029 ton/GJ, respectively.
