B.9 Real-time refinery predictive models

The high quality, and environmental friendly demands for gasoline products, combined with strong market competition and downward tendency of gasoline consumption, encourages the refiners to effectively reduce the amount of "give-away" for their gasoline products. On that account, minimisation of productivity cost function subject to optimum qualities of naphtha products from reforming and isomerization processes, together with gasoline blending, is of significant economical benefit.
The main objective of the Real-time Refinery Optimisation System (ROS) is to determine the targets for the process control system in such a way that the needed quantities of the different gasoline types can be produced on-time with the desired specifications in an economically optimal manner. An important basis for ROS is development of accurate predictive models for qualities of naphtha products, especially from reforming and isomerization processes. These models are mainly for prediction of Research Octane Number (RON), Reid Vapour Pressure (RVP), concentration of aromatic compounds, e.g. benzene, in the products, and ASTM distillation curve.
The types of predictive models in this work are ARX and ARMAX (Auto Regressive Moving Average with external input), i.e., parametric input-output representations. Since quality measurements are either expensive or delayed, only a limited number is available. Hence the need for predictive models is eminent.