A reduced fidelity model for the rotary chemical looping combustion reactor
MetadataShow full item record
AbstractThe rotary chemical looping combustion reactor has great potential for efficient integration with CO capture-enabled energy conversion systems. In earlier studies, we described a one-dimensional rotary reactor model, and used it to demonstrate the feasibility of continuous reactor operation. Though this detailed model provides a high resolution representation of the rotary reactor performance, it is too computationally expensive for studies that require multiple model evaluations. Specifically, it is not ideal for system-level studies where the reactor is a single component in an energy conversion system. In this study, we present a reduced fidelity model (RFM) of the rotary reactor that reduces computational cost and determines an optimal combination of variables that satisfy reactor design requirements. Simulation results for copper, nickel and iron-based oxygen carriers show a four-order of magnitude reduction in simulation time, and reasonable prediction accuracy. Deviations from the detailed reference model predictions range from 3% to 20%, depending on oxygen carrier type and operating conditions. This study also demonstrates how the reduced model can be modified to deal with both optimization and design oriented problems. A parametric study using the reduced model is then applied to analyze the sensitivity of the optimal reactor design to changes in selected operating and kinetic parameters. These studies show that temperature and activation energy have a greater impact on optimal geometry than parameters like pressure or feed fuel fraction for the selected oxygen carrier materials.
CitationIloeje CO, Zhao Z, Ghoniem AF (2017) A reduced fidelity model for the rotary chemical looping combustion reactor. Applied Energy 190: 725–739. Available: http://dx.doi.org/10.1016/j.apenergy.2016.12.072.
SponsorsThis study was financially supported by a grant from the MASDAR Institute of Science and Technology and the King Abdullah University of Science and Technology (KAUST) Investigator Award.