Open AccessOptimization of oil palm empty fruit bunch gasification temperature and steam to biomass ratio using response surface methodology
Author(s) -
N. H. A. Halim,
Suriyati Saleh,
Noor Asma Fazli Abdul Samad
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/702/1/012006
Subject(s) - response surface methodology , heat of combustion , yield (engineering) , biomass (ecology) , central composite design , pulp and paper industry , syngas , mathematics , materials science , chemistry , combustion , composite material , statistics , engineering , organic chemistry , agronomy , biology , hydrogen
An experimental work of empty fruit bunch gasification was conducted by using the bubbling fluidized bed to study the effect of the gasification temperature and steam biomass ratio (SBR) on the synthesis gas yield, Lower Heating Value (LHV) and Cold Gas Efficiency (CGE). Response Surface Methodology (RSM) was used to design the gasification experiment from the temperature range of 800 – 1000°C and SBR range of 0.5 – 1.5. Thirteen number of runs were generated based on Central Composite Design (CCD) with five replicated center points. Three regression models for predicting synthesis gas yield, LHV and CGE were developed and Analysis of Variance (ANOVA) was performed in this study. From ANOVA, the most influencing factor was gasification temperature which obtained higher F-value compared to SBR. The numerical optimization was also conducted in order to obtain the optimum condition to maximize the synthesis gas yield, LHV and CGE. From numerical optimization, gasification temperature of 800 °C and SBR of 1.14 were determined as the optimum condition which contributes to the maximum synthesis gas yield, LHV and CGE which are 1.25 Nm 3 /kg, 10.49 MJ/Nm 3 and 90.72% respectively. The percentage error between the predicted and actual value of response variables was calculated and the error obtained lesser than 1%. Thus, it confirmed that the models obtained can be used to optimize the gasification of the empty fruit bunch.