Improving VGO hydrotreater operation
A practical, industrial data-derived tool can give refiners confidence in simulating the actual benefits of additional hydrogen for improved VGO hydrotreater performance. A lumped parameter dynamic simulation modelling approach is employed
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A lumped parameter dynamic model, using both Microsoft Excel and AspenTech HYSYS software, for industrial refinery/upgrader vacuum gas oil (VGO) hydrotreaters has been developed from proprietary and public steady-state hydrotreater models. The model is based on industrial plant data and tracks changes in intrinsic reaction rates based on catalyst deactivation, wetting efficiency, feed properties and operating conditions to provide useful information, such as required operating temperature, outlet sulphur composition and chemical hydrogen consumed.
The model credibly simulates local disturbances and represents the three distinct operating zones during the hydrotreater run length: start-of-run (SOR), middle-of-run (MOR) and end-of-run (EOR). This correlative, partially predictive model can be applied to demonstrate the tangible economic benefits of increasing hydrogen use to improve the operation of a hydrotreater by increasing run length and/or improving crude processing.
Hydroprocessing has become a key refiner/upgrader operation due to two key developments. First, transportation regulations for refined products have evolved to significantly reduce the maximum amount of sulphur allowed (eg, <30 ppm gasoline in North America and <10 ppm diesel in Europe). Second, it is becoming necessary for refiners to process heavier, more sour crudes due to reduced availability of sweeter (low sulphur) crudes. As a consequence, there is a need to remove more sulphur than previously required.
Unfortunately, refiners/upgraders rarely achieve their run lengths and crude throughput objectives for VGO hydrotreaters.1 The performance shortfall is mostly due to disturbances (crude flow, feed compositional, sulphur, metals, and/or hydrogen partial pressure changes) that reduce the effectiveness of the catalysts. Most public domain dynamic hydrotreater research is based on pilot plant data that do not translate well to industrial applications. A key element of this tool’s development entailed gathering a substantial amount of relevant industrial data (14 operating industrial VGO units, with permission to publish data from six operators) specific to VGO hydrotreaters.
Methods and materials
The VGO hydrotreater model developed:
— Uses lumped parameters that match data available from industrial operations
— Uses a mix of industrial correlations, kinetic theory and academic research findings
— Factors in changes in operating conditions in response to disturbances in operation
— Incorporates changing reaction rate, wetting efficiency, catalyst deactivation in the three zones of the hydrotreater run life (ie, SOR, MOR and EOR)
— Uses parameters for all key process variables (sulphur, hydrogen partial pressure, temperature, hydrogen-to-oil ratio)
— Is run in dynamic mode to track the key variable product sulphur and the representative value of performance weighted average bed temperature (WABT)
— Incorporates familiar software (Excel and HYSYS) for easy translation into existing operations and acceptance by users
— Is correlation based, demonstrating semi-predictive tendencies
— Is used to represent a trickle fixed-bed reactor in operation.
Detailed industrial VGO hydrotreater data, under confidentiality agreement, were obtained and used from six operators. In addition, data from â€¨eight other plants was used in â€¨testing the developed model. Catalyst, process and laboratory data, plus equipment information were among the needed and gathered data. Table 1 provides a sample of the information gathered from the industrial operating units.
Dynamic approach â€¨to industrial â€¨hydrotreater kinetics
To dynamically track catalyst behaviour by calculating outlet sulphur â€¨composition from known or observed results of an industrial hydrotreater, the key product variable (Sp) was created in the form of Equation 1. The model involving Equation 1 takes into account process data, including temperature (T) and liquid hourly space velocity (LHSV) available from the plant data-gathering system; determines the impact of internal and external mass transfer resistance in a lumped parameter evaluation (ηe); and provides a relationship for catalyst deactivation embedded in the reaction rate expression khds:
In reviewing plant performance, pressure (P) and gas-to-oil ratio (G) were included in Equation 1, along with their respective exponential factors (p and g) to better model the operation. Note that the variables P and G are key contributors to hydrogen effectiveness in the hydrotreating reaction.
To address the lumped sulphur composition provided from the industrial units, dibenzothiophene (DBT) was chosen as the sulphur component on which to base the overall sulphur reaction kinetics. It is hypothesised that by using the slower DBT hydrogenation route to represent the overall sulphur conversion, treating all the sulphur as DBT should provide a representative conversion of all the sulphur. All the sulphur species that are easier to convert than DBT will be considered totally converted and lumped into the amount of DBT converted. The reversible dehydrogenation portion of this reaction provides a realistic representation of the reduced driving force of hydrodesulphurisation at higher temperatures.2
A crucial step in developing an accurate hydrotreater model is developing a realistic representation of catalyst deactivation and including it in the reaction rate expression (ki), illustrated in Equation 1. Overall, 30 correlations3 were modified or developed to provide the khds in Equation 1.
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