Controllable optimized designs of an ideal reactive distillation system using genetic algorithm

The steady state economic optimization to obtain the most economical controllable design of a double feed ideal reactive distillation (RD) column is demonstrated using real coded genetic algorithm. The novelty of the work is in the development of a simple procedure based on steady state criteria for controllability. The optimization is performed for four scenarios corresponding to a sequential increase in the number of design variables. Results show that limiting the optimization search space to only those designs that satisfy the controllability criteria leads to optimized designs that are only slightly (<2%) more expensive than the most economical design without controllability considerations. The former designs however exhibit much better controllability in terms of effectively handling a large through-put change using two-point temperature inferential control and avoiding a steady state transition under open loop operation. Results also show that the location of the fresh feeds is a dominant design variable with designs that do not constrain the feed tray location to be immediately above and below the reactive zone being substantially more economical.