Conceptual design and analysis of ITM oxy-combustion power cycles

Ion transport membrane (ITM)-based oxy-combustion systems could potentially provide zero-emissions power generation with a significantly reduced thermodynamic penalty compared to conventional carbon capture applications. This article investigates ITM-based oxy-combustion power cycles using an intermediate-fidelity model that captures the complex physical coupling between the two systems and accurately accounts for operational constraints. Coupled ITM-cycle simulation reveals hidden design challenges, facilitates the development of novel cycle concepts, and enables accurate assessment of new and existing power cycles. Simulations of various ITM-based zero and partial-emissions power cycles are performed using an intermediate-fidelity ITM model coupled to power cycle models created in ASPEN Plus®. The objectives herein are to analyze the prevalent ITM-based power cycle designs, develop novel design modifications, and evaluate the implementation of reactive ITMs. An assessment of the potential for these ITM power cycles to reduce both the thermodynamic penalty and reactor size associated with ITM air separation technology is conducted. The power cycle simulation and analysis demonstrate the various challenges associated with implementing reactive ITMs; hybridization (the use of both reactive and separation-only ITMs) is necessary in order to effectively utilize the advantages of reactive ITMs. The novel hybrid cycle developed herein displays the potential to reduce the size of the ITM compared to the best separation-only concept while maintaining a comparable First Law efficiency. Next, the merit of implementing partial-emissions cycles is explored based on a proposed linear-combination metric. The results indicate that the tradeoff between the main thermodynamic performance metrics efficiency and CO 2 emissions does not appear to justify the use of partial-emissions cycles. Hybridized ion transport membrane power cycles and detailed plant-level analysis using physics-based models and new performance metrics.