Abstract
Diesel hydro-processing (DHP) is an important refinery process which removes the undesired sulfur from the oil feedstock followed by hydro-cracking and fractionation to obtain diesel with desired properties. The DHP plant operates with varying feed-stocks. Also, changing market conditions have significant effects on the diesel product specifications. In the presence of such a dynamic environment, the DHP plant has to run in the most profitable and safe way and satisfy the product requirements. In this study, we propose a hierarchical, cascaded model predictive control structure to be used for real-time optimization of an industrial DHP plant.
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