Optimal selection of primary controlled variables for an acid gas removal unit as part of an IGCC plant with CO2 capture

This work is focused on the development of a rigorous, model based approach for the selection of primary controlled variables as part of a plant-wide control system design methodology. Selected controlled variables should exhibit good self-optimizing control performance while not sacrificing controllability. The approach developed in this work for the controlled variable selection problem results in a large-scale, mixed-integer optimization problem. For solution of this problem, a parallelized, bi-directional branch and bound (BNB) algorithm has been developed so as to solve the problem on large computer clusters, taking advantage of MATLAB^® Distributed Computing Server™. The proposed method is then applied to an acid gas removal (AGR) unit as part of an IGCC power plant with CO₂ capture.