Abstract
The use of biomass fuels in fluidized bed combustion (FBC) and gasification (FBG) is becoming more important because of the environmental benefits associated with these fuels and processes. However, severe bed agglomeration and defluidization have been reported due to the special ash forming constituents of some biomass fuels. Previous results have indicated that this could possibly be prevented by intelligent fuel mixing. In the present work the mechanisms of bed agglomeration using two different biomass fuels as well as the mechanism of the prevention of agglomeration by co-combustion with coal (50/50%w) were studied. Several repeated combustion tests with the two biomass fuels, alone (Lucerne and olive flesh), all resulted in agglomeration and defluidization of the bed within less than 30 minutes. By controlled defluidization experiments the initial cohesion temperatures for the two fuels were determined to be as low as 670°C and 940°C, respectively. However, by fuel mixing the initial agglomeration temperature increased to 950°C and more than 1050°C, respectively. When co-combusted with coal during ten hour extended runs, no agglomeration was observed for either of the two fuel mixtures. The agglomeration temperatures were compared with results from a laboratory method, based on compression strength measurements of ash pellets, and results from chemical equilibrium calculations. Samples of bed materials, collected throughout the experimental runs, as well as the produced agglomerated beds, were analysed using SEM EDS and X-ray diffraction. The results showed that loss of fluidization resulted from formation of molten phases coating the bed materials; a salt melt in the case of Lucerne and a silicate melt in the case of the olive fuel. By fuel mixing, the in-bed ash composition is altered, conferring higher melting temperatures, and thereby agglomeration and defluidization can be prevented.KeywordsHigh Melting TemperatureBiomass FuelNormal CombustionCompression Strength MeasurementScientific Group Thermodata EuropeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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