Former MASc Student
The development of clean energy production in order to mitigate the CO2 emissions is the main focus of actual research studies. Climate change, as a consequence of the excess of CO2 emissions from anthropological activities, is the most significant reason to develop new technologies in the energy sector. While renewable energies may be an attractive alternative resource of energy, carbon based power plants still remain as the main source of energy, and it will continue to do so for the coming decades. Post-combustion CO2 capture will play an important role on reducing this gas emissions. Also, it is a mature technology that can be easily integrated to existing power plants. However, this process still needs to be optimized in order to improve their efficient and minimize their impact on the operability and economics on the existing coal-based power plants.
The aim of my research is to analyze the controllability and dynamic operation of a post-combustion CO2 capture plant model using as main solvent Piperazine (PZ). The key in my research is to develop a Model Predictive Control (MPC) framework for this process. The proposed MPC scheme and this new promising solvent will be compared with previous studies to gain insight on the benefits and limitations on using MPC controllers and PZ solvent for post-combustion CO2 capture plants.
Thesis: Robust Optimization of a Post-combustion CO2 Capture Absorber Column under Process Uncertainty