(535b) Energy and Cost Estimation for CO2 Capture From Dry Flue Gas Using a Vacuum Swing Adsorption Process

There seems a consensus now that CO2 emissions to the atmosphere are a major cause for climate change. Nearly 40% of all the CO2 released annually to the atmosphere is from the fossil-fuel fired power plants. On an average, a 500 MW coal-fired power plant emits approximately 3 million tons of CO2 per annum [1]. Thus, the capture and concentration of CO2, especially from power-plant flue gas, is crucial. However, industrially, this remains a challenge because the energy and cost demanded by the capture process is prohibitive. Thus, it is imperative to develop an efficient and economical CO2 capture technology that can be readily retrofitted into existing power plants.

          Recent studies [2-5] suggest that an adsorption-based CO2 capture can significantly reduce energy penalty as compared to amine-based absorption. Haghpanah et al. [4, 5] presented a comprehensive study of a variety of VSA configurations and their performance for CO2 capture. However, most studies [2-5] in the literature have used specific energy consumption (kWh per tonne of CO2 captured) as the sole indicator for comparing various capture methods, and neglected the issues of capital expenditure and plant footprint, which can be equally critical. Recently, Hassan et al. [6] proposed a simplified strategy to estimate the cost of a PSA/VSA process for CO2 capture using a single column.

          In this work, we study and optimize in detail the best 4-step cycle identified by Haghpanah et al. [5] based on Zeochem zeolite 13X as the adsorbent for capturing CO2 from a dry flue gas. We use the comprehensive model of Haghpanah et al. [4] for simulating this process, which assumes dual-site Langmuir isotherm models and a linear driving force model for the gas-to-solid mass transfer. Owing to the high computational demand of the detailed model, we develop a surrogate model based on the Kriging approximation for the same and use that for optimization. The model based on kriging approximation enables us to do a constrained optimization. In addition, we develop an iterative algorithm that shuffles between the detailed and surrogate models for our single objective optimization. We present a detailed analysis of the various design and operational factors that affect the minimum energy required to capture CO2 with a purity of 90 mol% purity and a recovery of 90% from a dry flue gas using the proposed adsorption process. Also, we also determine the trade-off between energy, purity, recovery, and productivity for feeds from various emission sources. Furthermore, we examine the advantages of multi-stage separation. Finally, we present a procedure to design and operate a multi-column capture system for dry flue gas from a 500 MW coal-fired power plant and develop a mixed integer non-linear programming (MINLP) formulation based on the kriging approximation model to minimize the total annualized cost. We solve this MINLP model in GAMS using IPOPT and the detailed model in MATLAB to analyse the relative importance of energy consumption, land cost, adsorbent cost, plant footprint, operating expenditure (OPEX), and annualized capital expenditure (CAPEX) for such a capture plant.

References

[1]   The future of coal: options for a carbon-constrained world. Massachusetts Institute of technology, Cambridge, MA, 2007.

[2]   Dowling AW, Vetukuri SRR, Biegler LT. Large‐scale optimization strategies for pressure swing adsorption cycle synthesis. AIChE Journal. 2012; 58.12: 3777-3791.

[3]   Zhang J, Webley PA, Xiao P. Effect of process parameters on power requirements of vacuum swing adsorption technology for CO2 capture from flue gas. Energy Conversion and Management. 2008; 49(2), 346-356.

[4]   Haghpanah R, Majumder A, Nilam R, Rajendran A, Farooq S, Karimi IA, Amanullah M. Multi-objective Optimization of a 4-step Adsorption Process for Post-combustion CO2 Capture Using Finite Volume Technique. Industrial & Engineering Chemistry Research. 2013; 52(11), 4249-4265.

[5]   Haghpanah R, Nilam R, Rajendran A, Farooq S, Karimi IA. Cycle Synthesis and Optimization of a VSA Process for Post-combustion CO2 Capture. AIChE Journal. Under review, 2013.

[6]   Hasan MMF, Baliban RC, Elia JA, Floudas CA. Modeling, Simulation, and Optimization of Postcombustion CO2 Capture for Variable Feed Concentration and Flow Rate. 2. Pressure Swing Adsorption and Vacuum Swing Adsorption Processes. Industrial & Engineering Chemistry Research. 2012; 51.48, 15665-15682.