Abstract:
Carbon dioxide is a prominent greenhouse gas whose emissions have significantly
increased due to human activities. Fossil fuel-fired power plants are the largest source of
CO2 emissions, which results in a need for CO2 capture at these power plants. Prior to
building a large scale CO2 capture plant, a pilot or demonstration plant is set up to
confirm the feasibility of the plant. Simulation techniques are needed before actually
constructing the plant, in order to improve the reliability and to increase productivity. A
number of simulation software tools have been developed and are widely used to
complete the simulation of a power plant integrated with a CO2 capture plant. Therefore,
the capability of the software to model and simulate the plant correctly, and to generate
accurate and reliable results, is of particular importance.
In this work, the performance of two of the most commonly used process simulators for
CO2 capture, namely ASPEN Plus and PROMAX, was evaluated and compared. In order
to achieve this goal, eight data series from two CO2 capture pilot plants were selected and
simulated with the above-mentioned simulators. The pilot plant data came from the
International Test Centre for CO2 Capture (ITC) and the Esbjerg CO2 from Capture to
Storage (CASTOR) project. Simulations were compared to experimental results using
several parameters, including CO2 recovery, lean and rich loadings, steam and heat
duties, CO2 percentage in the product stream, and the temperature and concentration
profiles in the columns. Results showed that both software packages could predict the
behavior of the system accurately and generate reliable results. The obtained results
showed that in most cases, particularly in predicting the absorber and stripper profile along the column, PROMAX generated results that were closer to the actual experimental
data, when compared to ASPEN.
Description:
A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. ix, 72 l.