The Application of a Model Predictive Control-Based Approach to CO2 Capture Processes: Towards Operational Cost Minimisation

Amine-based chemisorption of CO₂ is a promising near term option for the decarbonisation of large, fixed-point CO₂ emission sources[1]. However, the operational expenditure (OPEX) associated with this technology imposes a significant energy penalty on the power plant. As it is the solvent which determines the thermodynamic and kinetic efficiency of the process, the design of advanced solvents provides a real opportunity to reduce the OPEX. Typically, when one refers to the dynamic operation of CCS-type processes, it is the transient behaviour of the start-up and shut-down of this process which is considered. However, the so-called steady-state operation of power-plants is itself dynamic, i.e., the flowrate, temperature and composition of the inlet flue-gas can vary in real time. Thus, a given solvent and mode of process operation which may be optimal for a particular operating regime, may be sub-optimal for another operating regime. Consequently, the implementation of advanced control strategies present an important opportunity for the intensification of these processes resulting in a significant reduction in the lifetime operational expenditure associated with CCS systems.

This work focuses on the design of an explicit model predictive controller (MPC)[2] for the real-time control of solvent composition and process operation as successfully implemented in other applications such as [3].To achieve this, we integrate molecular-based fluid theories[4] with high-fidelity process models[5]. Based on this model, an approximate model is developed and a model predictive controller is formulated for the reduced model where our multi-parametric algorithms are applied to derive a suitable and robust explicit MPC controller. By incorporating the explicit controller expressions (control laws) in the original model, a validation step is then carried out.

In this way, we present a unified-systems based methodology for the OPEX reduction of solvent-based post-combustion CO₂ capture processes.