Optimization of industrial-scale pre-combustion CO2-capture unit of an IGCC power plant



This study is part of a larger research project which is focused on the exploitation of CCS technology to minimize CO2 emissions from IGCC power plants. To study issues related to the incorporation of this new technology into IGCC plants, the utility company Nuon/Vattenfall realized a CO2 capture pilot plant (Figure 1) at the site of the Buggenum IGCC power station. The CO2-capture unit is integrated within the entire power plant downstream of the gasifier. With a special syngas treatment (CO shifting and CO2 absorption) the feedstock’s carbon inventory can be effectively captured and then buried underground. This technology is known as pre-combustion carbon capture.     

One of the major drawbacks of the integration of CO2 capture technology into power plants for energy production is the penalty on the overall efficiency which is estimated to be in a range of 9-12% points. Therefore, the successful introduction of capture technology will also depend on, among other issues (political, environmental, technical), the ability to reduce this energy penalty. System analysis and optimization will help to determine the most energy-efficient operation.



Involved People:

Facilities used:




This study is focused on the determination of the most energy and cost efficient operational point of the CO2 capture unit comprising of the shifting and absorption section. The state-of-the-art approach to this type of study is by means of steady-state modelling of the process, system analysis and process optimization.



The general objectives can be summarized as follows:


  • Scale-up of existing CO2 capture pilot plant model in order to obtain industrial-scale model

  • Definition of decision variables for the optimization problem

  • Formulation of single or multi objective function representing energy consumption and cost

  • Development of optimization framework (choice of most suitable optimization algorithm, integration of optimizer and process simulator)

  • Performance of global optimization

  • Result analysis (one or multiple optimal operational sets)




Work program


The existing and validated pilot plant model shall be used as starting point for the development of the large-scale capture unit. The topology of the process will be based on an available preliminary design study carried out during the project. Changes in the configuration of the process will not be considered throughout the optimization, only the operational parameters shall be optimized. This will simplify the optimization as no mixed integer variables are involved.


The first step of the optimization process is to define the decision variables which will be optimized in order to minimize or maximize the objective function. The boundaries of the decision variables need to be defined (operational range) as well as the boundaries of other important process variables (for instance product quality, temperature safety limits, etc.). Further, the objective function needs to be defined. The main objective is the reduction of the energy penalty introduced to the power conversion process by the added capture process. An energy optimization problem is commonly formulated in terms of overall exergy efficiency or exergy destruction. It should also be considered to include costs (educts, products, equipment) in the objective function. For instance, the CO2 capture rate should be represented in the objective function. The optimization problem can then be formulated as a single objective or multi-objective problem. A multi-objective optimization would identify the trade-off between the objectives in a clear manner. Though, this optimization comes at a higher cost for complexity.

The optimization shall be performed in an automated way. Hence, a framework needs to be developed which integrates the process simulator (Aspen Plus) and an optimization tool (egMatlab or Tomlab), which provides advanced, multi-variable, gradient-free algorithms. Among the various algorithms the most suitable one in terms of effectiveness (finding global optimum) and efficiency (calculation time) has to be identified.

The result of the optimization will be one or multiple optimal set(s) of operational parameters for the large-scale capture unit. The simulation results employing the optimized parameters will be compared with the performance data for the preliminary design operation. A further result analysis should identify if topological changes might be meaningful. The methodology and developed tool structure could then easily be applied for the optimization of other possible configurations of the capture unit. Hence, different designs could be optimized and compared.





The study will be closely supervised by Prof. Dr. Piero Colonna and Dipl.-Ing. Carsten Trapp. The duration of the study is intended to be 6 months full-time.





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