(185u) Development of a One-Dimensional Bubbling Fluidized Bed Model for a Coal-Fed Chemical Looping Combustion Fuel Reactor
AIChE Annual Meeting
2018
2018 AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Design
Monday, October 29, 2018 - 3:30pm to 5:00pm
CLC provides some advantages for the generation of low carbon energy, as the CLC process produces a CO2 rich flue gas without the additional energy and capital costs associated with post-combustion capture from conventional fossil-based power plants, thus potentially leading to lower costs of electricity in comparison to conventional capture processes.
Past CLC research primarily focused on gaseous fuels; however, in the last decade there has been an increasing emphasis on adapting chemical looping technology for the direct combustion of solid fuels such as coal and biomass. The direct CLC of solid fuels avoids the extra processing step associated with the indirect CLC of solid fuels where gasification of the solid fuel to syngas (mainly CO2 and H2) is done before the CLC of the resulting syngas. Though the potential for direct CLC of solid fuels like coal have been successfully demonstrated in several pilot scale demonstration facilities, there have been no commercial scale plants to date (Adanez et al. 2018).
One way to accelerate the development of CLC technology is through the use of mathematical models. These models can provide a representation of the physical phenomena that might be difficult or expensive to measure in physical models. Furthermore, these models can be used as part of plant-scale modeling studies to identify optimal design and operating conditions for further investigation in bench and pilot-scale experiments.This work presents the development of a steady-state, one-dimensional, bubbling fluidized bed model of a coal-fed CLC fuel reactor that is suitable for both simulation and optimization type studies. Mass and energy balances of the gas and solid phases in the model are developed from first principles, while semi-empirical correlations are used for hydrodynamic, mass and heat transfer computations. The methodology used for this model development effort is adapted from prior work on gas-fired CLC (Okoli et al. 2018), with changes made to the reaction and hydrodynamic sub-models to account for the use of a solid fuel. The resulting model consists of a set of differential algebraic equations, and accounts for the gas and solid phase interactions in the reactor, such as the devolatilization and gasification reactions of coal, as well as the reactions between the OC and the evolved gases from the coal reactions. Furthermore, the model considers the mass and heat diffusion phenomena occurring in the bubble, cloud-wake and emulsion regions of the reactor. The output of the model includes the axial profiles of the pressure, velocities, concentrations, flows and temperatures in the reactor.
The modelâs capabilities are demonstrated for the simulation of different coal-fed CLC fuel reactor configurations with an iron-based OC. In addition, the impacts of key design variables on the reactorâs performance are also evaluated.
The model is built using the Institute for the Design of Advanced Energy Systems (IDAES) open-source equation-oriented process systems engineering framework which enables the rapid development and optimization of next generation advanced energy systems (Miller et al. 2018). Its modular nature allows for easy reuse and integration of different models and solvers, thus allowing the quick assembly of flowsheets for large scale simulation and optimization studies. The IDAES platform utilizes Pyomo (Hart et al. 2017); a Python based algebraic modeling language and incorporates the object-oriented features of Python.
References
J. Adanez, A. Abad, T. Mendiara, P. Gayan, L.F. de Diego, F. Garcia-Labiano, 2018. Chemical looping combustion of solid fuels, Progress in Energy and Combustion Science, 65, 6 - 66.
W.E. Hart, C. D. Laird, J. P. Watson, D. L. Woodruff, G. A. Hackebeil, B. L. Nicholson and J. D. Siirola, 2017, Pyomo â Optimization Modeling in Python, 2nd ed., Springer, Vol. 67.
D.C. Miller, J.D. Siirola, D.A. Agarwal, A.P. Burgard, A. Lee, J.C. Eslick, B.L. Nicholson, C.D. Laird, L.T. Biegler, D. Bhattacharyya, N.V. Sahinidis, I.E. Grossmann, C.E. Gounaris, and D. Gunter, 2018. Next Generation Multi-Scale Process Systems Engineering Framework, Proceedings of the 13th International Symposium on Process Systems Engineering, San Diego, California, USA.
C.O. Okoli, A. Lee, A.P. Burgard, D.C. Miller, 2018. A fluidized bed process model of a chemical looping combustion fuel reactor, Proceedings of the 13th International Symposium on Process Systems Engineering, San Diego, California, USA.