A superstructure-based optimal synthesis of PSA cycles for post-combustion CO2 capture

Authors

  • Anshul Agarwal,

    1. Collaboratory for Process and Dynamic Systems Research, National Energy Technology Laboratory, Morgantown, WV 26507
    2. Chemical Engineering Dept., Carnegie Mellon University, Pittsburgh, PA 15213
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  • Lorenz T. Biegler,

    Corresponding author
    1. Collaboratory for Process and Dynamic Systems Research, National Energy Technology Laboratory, Morgantown, WV 26507
    2. Chemical Engineering Dept., Carnegie Mellon University, Pittsburgh, PA 15213
    • Collaboratory for Process and Dynamic Systems Research, National Energy Technology Laboratory, Morgantown, WV 26507
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  • Stephen E. Zitney

    1. Collaboratory for Process and Dynamic Systems Research, National Energy Technology Laboratory, Morgantown, WV 26507
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  • This is a U.S. Government work and, as such, is in the public domain in the United States of America.

Abstract

Recent developments have shown pressure/vacuum swing adsorption (PSA/VSA) to be a promising option to effectively capture CO2 from flue gas streams. In most commercial PSA cycles, the weakly adsorbed component in the mixture is the desired product, and enriching the strongly adsorbed CO2 is not a concern. On the other hand, it is necessary to concentrate CO2 to high purity to reduce CO2 sequestration costs and minimize safety and environmental risks. Thus, it is necessary to develop PSA processes specifically targeted to obtain pure strongly adsorbed component. A multitude of PSA/VSA cycles have been developed in the literature for CO2 capture from feedstocks low in CO2 concentration. However, no systematic methodology has been suggested to develop, evaluate, and optimize PSA cycles for high purity CO2 capture. This study presents a systematic optimization-based formulation to synthesize novel PSA cycles for a given application. In particular, a novel PSA superstructure is presented to design optimal PSA cycle configurations and evaluate CO2 capture strategies. The superstructure is rich enough to predict a number of different PSA operating steps. The bed connections in the superstructure are governed by time-dependent control variables, which can be varied to realize most PSA operating steps. An optimal sequence of operating steps is achieved through the formulation of an optimal control problem with the partial differential and algebraic equations of the PSA system and the cyclic steady state condition. Large-scale optimization capabilities have enabled us to adopt a complete discretization methodology to solve the optimal control problem as a large-scale nonlinear program, using the nonlinear optimization solver IPOPT. The superstructure approach is demonstrated for case studies related to post-combustion CO2 capture. In particular, optimal PSA cycles were synthesized, which maximize CO2 recovery for a given purity, and minimize overall power consumption. The results show the potential of the superstructure to predict PSA cycles with up to 98% purity and recovery of CO2. Moreover, for recovery of around 85% and purity of over 90%, these cycles can recover CO2 from atmospheric flue gas with a low power consumption of 465 k Wh tonne−1 CO2. The approach presented is, therefore, very promising and quite useful for evaluating the suitability of different adsorbents, feedstocks, and operating strategies for PSA, and assessing its usefulness for CO2 capture. Published 2009 American Institute of Chemical Engineers AIChE J, 2010

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