Modeling and Control of Benzene Hydrogenation via Reactive Distillation.

Automotive emissions are a significant contributor to degeneration of air quality. As such, specifications for automobile fuels obtained from petroleum have received increasing levels of attention from the Environmental Protection Agency (EPA). One compound that is regulated is benzene. Being a carcinogen, the United States Environmental Protection Agency (EPA) requires all refiners to limit the amount of benzene in gasoline to 0.62 vol% [1]. The main source for producing benzene in a gasoline pool is the reformer unit and thus benzene is present in significant amounts in the reformate stream. This work focusses on treatment of benzene present in the reformate stream.

One option to remove benzene is to hydrogenate in presence of a catalyst. However, a problem arises as the catalyst used for the reaction is not selective for benzene, and toluene, which is present in the reformate stream in considerable quantities, will also be hydrogenated. Toluene hydrogenation is undesirable as toluene has a high octane rating (RON) and, should be retained in the final product.

In order to avoid problems related to the selectivity of the catalyst, the reformate stream is split into light and heavy components in the conventional process. As benzene is a reasonably light component, it is mostly concentrated in the distillate, which is then hydrogenated before being sent back to the gasoline pool. The downside of this process is that a high capital investment is needed. Reactive distillation offers an alternative route for solving this problem. By combining reaction with separation it is possible to selectively react one component in a specified region of the column while suppressing unwanted reactions of other components. Furthermore, additional savings can be achieved as the heat of reaction can be directly used for separation of the mixture [2, 3].While reactive distillation can have significant advantages over traditional designs, there are also downsides that need to be considered. For example, the simultaneous presence of reaction and separation phenomena can result in complex dynamic behavior. As such, it is important to conduct a thorough investigation of the dynamics of as well as of control configurations for reactive distillation columns to determine their viability for a particular process.

The reactive distillation column investigated in this work is a packed bed column with 70 theoretical stages and the mixture to be separated includes 15 components. A detailed fundamental model has been developed in gPROMS. The model consists of over 2400 differential equations and over 4500 algebraic equations. The column also involves a partial condenser and a recycle stream which pose additional challenges to the model due to the resulting different time scales of the dynamic behavior. A further complicating factor is that the compositions of the product streams are not the only important measures for performance of the process: one aim is to reduce the benzene concentration to acceptable levels, while at the same time as little toluene as possible should be converted.

The model was evaluated in a series of simulations involving commonly occurring disturbances, e.g., feed composition variations. A transfer function model was developed from the responses and a multi-loop control configuration was designed. The controllers were then applied to the rigorous column model and the column under feedback control was evaluated in a series of simulations. It was shown that the control scheme can result in good performance except for the case where significant feed composition disturbances are present. A feedforward-feedback control scheme was developed to address this point. The addition of feedforward control was able to reject feed concentration disturbances as long as the feed composition measurements only included small or no time delays. This work highlights that this type of process can be well controlled using traditional control schemes, however, good performance requires small measurement time delays .