Process Simulation of Dual Fluidized Bed Gasifiers Using Experimental Data

Journal article, 2016

Process simulation of a dual fluidized bed (DFB) gasifier is challenging, owing to the high degree of freedom inherent to the operation of the double-reactor system and the complexity of the reactions therein. We propose a method for simulation of the gasifier based on the analysis of experimental data and of the total uncertainty associated with them. The overall aim is to use data from the large amount of pilot and demonstration gasifiers in the analysis and optimization of gasification-based processes. In the method proposed a set of fuel conversion variables and their associated uncertainties are calculated using a stochastic approach that takes into account the effect of unclosed mass balance, incomplete characterization of the raw gas compounds and measurement errors. Subsequently, these fuel conversion variables are used to simulate the gasifier in a flowsheet model developed in Aspen Plus. The results include the evaluation of critical parameters, such as, gasifier efficiency, char gasification, and tar yield and their uncertainties, which depend highly on the measurement system. The method is applied to data sets derived from several measurement setups, and the results are validated with total carbon measurements. The results show that detection of ≥95% of the carbon in the raw gas is necessary to maintain the uncertainty level at <3% and to estimate the char conversion and oxygen transport. The flowsheet model of the gasifier is applied to a database of six operational points; the results show that interpolation and extrapolation of the fuel conversion variables are possible and the gasifier is evaluated in operational conditions different from the experiments. In summary, this method is flexible with respect to different measurement setups and represents a valuable tool for process simulation using flowsheet software.