Multi-parameter optimization of double-loop fluidized bed solar reactor for thermochemical fuel production

In this paper, the design of a double-loop fluidized bed solar reactor, involving CeO2 nanoparticles and two gas streams of N2 and CO2, for efficient thermochemical fuel production, has been optimized in a six-dimensional parameter space by means of a multi-parameter optimization algorithm. The system under investigation is capable to develop a thermochemical two-step cycle, producing CO by means of the overall reaction CO2→CO+1/2O2. The use of nanoparticles as catalyst allows maximizing the performance of the reactor; actually, nanoparticles increase surface area of reaction, with respect to common catalysts and, at the same time, allow realizing the reactor as double-loop fluidized bed, which can operate without alternating flows of CO2 and inert sweep gas. A genetic algorithm coupled with a quasi-random Sobol design population has been used, to find the optimal configuration of the double-loop fluidized bed solar reactor. The results highlighted the very important role of several factors, as radius of fluidized beds, mean residence time of reactor, mass of nanoparticles within reactor, solar concentration ratio, etc., on the performance of the system under investigation and allowed to find the best configuration of the system, reaching the mean global efficiency over a period of time of 1 year equal to 29.96%, with a maximum of 59.46%.