Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 735-744 |
| Journal | Energy Conversion and Management |
| Volume | 86 |
| DOIs | |
| Publication status | Published - 2014 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- biodiesel
- biofuels
- glycerol
- olefins
- catalytic conversion
- process optimization
- response surface methodology