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Simulation and Model Predictive Control of CO2 Capture Plants From Flue Gas

Mohammad Aminpour, Shahram | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52948 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Pishvaie, Mahmoud Reza
  7. Abstract:
  8. Continued uncontrolled gas emission can cause extreme changes in climate all over the world and threaten the life So, the removal and/or reduction of CO2 from the atmosphere is essential to prevent its side effects. CO2 separation is the costliest part of the gas removal process from fossil fuel combustion. Among several available CO2 capture technologies, the MEA-based post-combustion CO2 capture process is considered a mature technology for mitigating CO2 emissions. In this study a steady-state MEA-based CO2 capture process from the coal power plant is developed in Aspen Plus. Subsequently, steady-state model with appropriate modifications, is exported into Aspen Plus Dynamics to study transient characteristics and to design the control system. The need to develop advanced model-based control systems was observed to maintain the dynamic performance of the coal power plant in the presence of various operating constraints and disturbances. Therefore, a model predictive controller (MPC) was designed and implemented using Aspen Plus Dynamic and Simulink MATLAB. In the control studies, the performance of proportional-integral (PI) controllers and model predictive controller was investigated. The case studies presented in this study show that MPC performs significantly better when compared to a decentralized multi-loop control scheme based on proportional-integral(PI) controllers
  9. Keywords:
  10. Model Predictive Control ; Sensitivity Analysis ; Dynamic Simulation ; Carbon Dioxide Separation ; Steady State Simulation

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