Response surface methodology (RSM) and multi-objective genetic algorithm was employed to optimize the process parameters for catalytic conversion of glycerol, a byproduct from biodiesel production, to light olefins using Cu/ZSM-5 catalyst. The effects of operating temperature, weight hourly space velocity (WHSV) and glycerol concentration on light olefins selectivity and yield were observed. Experimental results revealed the data adequately fitted into a second-order polynomial model. The linear temperature and quadratic WHSV terms gave significant effect on both responses. Optimization of both the responses indicated that temperature favouring high light olefin formation lied beyond the experimental design range. The trend in the temperature profile concurred commensurately with the thermodynamic analysis. Multi-objective genetic algorithm was performed to attain a single set of processing parameters that could produce both the highest light olefin selectivity and yield. The turn-over-frequency (TOF) of the optimized responses demonstrated a slightly higher value than the one which was not optimized. Combination of RSM, multi-objective response and thermodynamic is useful to determine the process optimal operating conditions for industrial applications.
|Journal||Energy Conversion and Management|
|Publication status||Published - 2014|
|MoE publication type||A1 Journal article-refereed|
- catalytic conversion
- process optimization
- response surface methodology