Lu Donghui, Lope G. Tabil, Wang Decheng, Wang Guanghui, Wang Zhiqin. Optimization of binder addition and compression load for pelletization of wheat straw using response surface methodology[J]. International Journal of Agricultural and Biological Engineering, 2014, 7(6): 67-78. DOI: 10.3965/j.ijabe.20140706.009
Citation: Lu Donghui, Lope G. Tabil, Wang Decheng, Wang Guanghui, Wang Zhiqin. Optimization of binder addition and compression load for pelletization of wheat straw using response surface methodology[J]. International Journal of Agricultural and Biological Engineering, 2014, 7(6): 67-78. DOI: 10.3965/j.ijabe.20140706.009

Optimization of binder addition and compression load for pelletization of wheat straw using response surface methodology

  • Abstract: Densification is required for efficiently handling and transporting biomass as feedstock for biofuel production. Binders can enhance straw pellet strength and improve the pellet performance. The present investigation aimed to optimize binders and compression load for wheat straw pelletization using a single pelleting unit. Response surface methodology was employed by using a four-factor, five-level central composite design with wood residue (%, w/w), bentonite (%, w/w), crude glycerol (%, w/w), and compression load (N) as process parameters. The pellet tensile strength, specific energy consumption of pelleting, and pellet density were the response variables. The higher heating value, ash content of the pellet product and the cost of the feedstock were also considered in optimizing binder addition. The developed model fitted the data and was adequate for binder analysis and optimization. Wheat straw pellet, with the addition of 30% wood residue, 0.80% bentonite, and 3.42% crude glycerol, in addition to 4 000 N of compressive load, was identified as optimal with good performance of pellet tensile strength (1.14 MPa), specific energy consumption (32.6 kJ/kg), and pellet density (1 094 kg/m3) as well as low ash content (6.13%) and high heating value (18.64 MJ/kg). Confirmation tests indicated high accuracy of the model.
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