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Author:Ji, Xiaoyun
Title:Simulation and analysis of an integrated steam pyrolysis system
Publication type:Master's thesis
Publication year:2013
Pages:(15) + 120 s. + liitt. 18      Language:   eng
Department/School:Energiatekniikan laitos
Main subject:Energiatekniikka   (Ene-47)
Supervisor:Järvinen, Mika ; Yang, Weihong
Instructor:Kohl, Thomas ; Kantarelis, Efthymios
OEVS:
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Location:P1 Ark Aalto  6205   | Archive
Keywords:bio-oil
pyrolysis enthalpy
steam pyrolysis
system integration
Abstract (eng): The conceptual design of an integrated system for steam pyrolysis is presented.
For the biomass input of 1 kg, pyrolysis enthalpy of 1639 kJ resulted from calculation is discussed as a reasonable estimation for pyrolysis of softwood.
Four cases of pyrolysis using steam and nitrogen were simulated.

Overall, for the combustion bed temperature of 850°C, if there is sufficient steam for the low-pressure steam turbine, all steam pyrolysis systems can always operate self-sufficiently.
Additionally, if a high preheated air temperature is required, partial char combustion can be better deployed for steam pyrolysis than in the case of conventional N2 operation.

Moreover, the steam-to-biomass mass ratios determine the capacities of turbines and a low steam-to-biomass mass ratio contributes to a stable electricity output.
Only when the pyrolysis enthalpy is estimated to be above 2.0 MJ per kg of biomass input, the highest electricity output is attributed to the case of N2.
Otherwise, with the same combustion bed temperature and same pyrolysis enthalpy, the case for steam-to-mass ratio of 0.34 always represents highest electricity output.
For a biomass input of 3 kg/s, the system can generate approximately 3 MW of excess power.

As preliminary optimization results, three integrated systems with steam-to-biomass mass ratios of 0.34, 0.67 and 0.5 are proposed as optimum cases under electricity-, bio-oil-and operation-dominated scenario designs.
Moreover, the system with steam to biomass mass ratio of 0.5 can be considered as the candidate for future multi-objective optimization results.
ED:2013-10-16
INSSI record number: 47319
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