PROCEEDINGSof the 6th International Conference on Chemical Technology

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16. – 18. 4. 2018Mikulov, Czech Republic

6th International Conference on Chemical Technology

www.icct.cz

330 ICCT 2018 | PROCEEDINGS

PETROCHEMICALS AND ORGANIC TECHNOLOGY

IMPROVEMENTS IN TEMPERATURE CONTROL SYSTEM OF RESIDUAL HYDROCRACKER UNIT Janošovský J., Bartoš M., Labovský J. Institute of Chemical and Environmental Engineering, Slovak University of Technology, Radlinského 9, 812 37 Bratislava, Slovakia jan.janosovsky@stuba.sk

Abstract RHC (Residual HydroCracker) reactors are very complex reactive systems requiring appropriate level of process control. The presented analysis was performed on an industrial residue hydrocracking cascade system consisting of three ebulated-bed RHC reactors connected in series with reaction temperature ranging from 405 to 420 °C at the pressure of 18-20 MPa. One RHC reactor was equipped with ca. 200 thermocouples distributed unevenly on the reactor jacket and in the main flow core. In this paper, an improved reactor temperature control system based on the construction of 3D temperature profile is proposed. The presented visualisation tool provided 2D and 3D projections of temperature profile in each of the three RHC reactors. Different interpolation techniques had to be applied to assign temperature values in spatial points without thermocouples and the calculation results were evaluated with the emphasis on the quality of the resulting temperature profile. Examples of the obtained temperature profile for different interpolation techniques are also provided. With the help of our tool, potential cold and hot spots damaging catalyst were identified and approximate flow patterns of the reaction mixture were distinguished.

Introduction Crude oil is an unrefined liquid mixture of hydrocarbons and other organic materials naturally found within the Earth. It is used mostly as an energy source in fuel industry, but also as a source of ethylene, propylene, benzene and other valuable intermediate products. Components of crude oil can be divided into several fractions as shown in Table I based on different boiling points1. Table I Crude oil fractions

Fraction Boiling point [°C] Hydrocarbons fraction gases < 1 C1 - C4

light naphtha 30 – 85 C5 - C6 heavy naphtha 90 – 180 C7 - C10

kerosene 180 – 300 C11 - C15 light gas oil 200 – 350 C16 - C20

heavy gas oil 350 – 550 C21 - C45 residue > 550 > C45

The first step of crude oil processing represents atmospheric distillation column where gases, gasoline, naphtha, gas oil and atmospheric residue are separated. The atmospheric residue is further distilled in a vacuum distillation column. The bottom product of vacuum distillation, heavy residue, consists of hydrocarbon fractions that contain organic compound with high molecular weight, metals, sulphur compounds and asphaltenes. These components are relatively low value chemicals, but can be upgraded into more valuable products by various enrichment processes such as hydrocracking1. Hydrocracking converts high-boiling hydrocarbons to lower-boiling products by catalytic cracking in the presence of hydrogen in a residual hydrocracker (RHC) reactor. RHC reactor under review operated at temperature of 400 - 420 °C and pressure of 18 - 20 MPa. Ni-Mo/Al2O3 catalyst was used to crack the heavy molecules into lighter ones. The reaction mixture was contacted with catalyst in the form of ebullated bed to overcome problems with catalyst deactivation, coke formation and instability caused by the presence of heavy metals. Ebullation was maintained by continuous feeding of fresh catalyst with reaction mixture and high-pressure hydrogen into the reactor, while the deactivated catalyst was continuously removed for regeneration2. Part of the processed feed was recycled back in the reactor to adjust hydrodynamic regime. The conversion mechanism in the reactor is composed from several chemical reactions including heavy residue (HR) cracking into off gasses (G), naphtha (GLN), kerosene (Ke), gas oil (GO) and vacuum distillates (VGO) and secondary cracking of VGO into GO, GLN and Ke. The proposed reaction scheme3 is depicted in Figure 1. Two main thermal processes are endothermic hydrocarbon cracking and exothermic hydrogenation.

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Overall heat effect of the process is slightly exothermic, but the heat is easily dissipated. With the amount of chemical reactions occurring in the reactor, temperature represented an important process parameter to be measured and to be used for appropriate control of such complex reactive system. Higher temperature was favored to increase yield of desired products; however, the temperature increase was limited due to the increasing coke formation. Stagnant zones might develop in reactor as well, thus precise temperature control was necessary.

Figure 1. Reaction pathways in the RHC reactor under review3 Approximately 200 installed thermocouples per reactor were scattered on the jacket and in the core of the studied cascade of three RHC reactors. The aim of the presented work to compare different data interpolation methods to calculate temperature values inside the whole reactor and to visualize accurate temperature profile in 2D and 3D space. Obtained visualizations represented fundamental basis for improved process control and optimization. Furthermore, the process safety could be improved by supporting decision-making of the process engineers and operators. Visualized temperature profiles were suitable for direct incorporation into control panel display. Appropriate alignment and clarity of displayed process information make operation data more accessible for the operators and could be crucial to avoid emergency reactor shutdowns and hazardous events4.

Methodology MATLAB software environment was employed to interpolate measured temperature data and to visualize a temperature profile inside the reactor. Firstly, information containing thermocouples position within the reactor had to be processed from P&ID schemes to the form suitable for data storage in MATLAB structures. In the next step, measured temperature data had to be loaded. The company operating RHC reactors under review uses Microsoft Excel spreadsheets for measured data extraction and analysis. Therefore, a communication mechanism between MATLAB and Microsoft Excel was constructed. For temperature profile visualization, a fine uniform grid of points was created in both directions, horizontal and vertical. Then, the temperature was calculated for every grid point by interpolating measured temperature data. The initial analysed interpolation method was the basic method of nearest neighbor interpolation. Firstly, Euclidean distance di from every thermocouple to one particular grid point was calculated. In the next step, the Euclidean distances were sorted from the closest one to the furthest one. Temperature of the closest thermocouple was then assigned to the grid point. Every grid point underwent the same procedure. To estimate grid point value by considering multiple thermocouples, the inverse distance weighting (IDW) method5 was applied. In this procedure, factor hi was calculated based on the value of Euclidean distances and the exponent k as shown in Equation 1. Factor hi was then used to calculate weights wi (Equation 2) of chosen number of thermocouples. The number of thermocouples was optional. Based on the weights and measured temperature data 𝑇𝑇𝑖𝑖𝑚𝑚, temperature �̅�𝑇𝑖𝑖 of a query point was calculated (Equation 3). The algorithm was repeated for every grid point. ℎ𝑖𝑖 = 1

(𝑑𝑑𝑖𝑖)𝑘𝑘 (1)

𝑤𝑤𝑖𝑖 = ℎ𝑖𝑖∑ ℎ𝑖𝑖𝑛𝑛𝑖𝑖=1

(2)

�̅�𝑇𝑖𝑖 = ∑ 𝑤𝑤𝑖𝑖 × 𝑇𝑇𝑖𝑖𝑚𝑚𝑛𝑛𝑖𝑖=1 (3)

For more detailed analysis, advanced interpolation methods based on Delaunay triangulation and Voronoi diagrams that are recommended for scattered data interpolation were tested. The typical results of Delaunay

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PETROCHEMICALS AND ORGANIC TECHNOLOGY

triangulation in a plane are depicted in Figure 2. In a plane, Delaunay triangulation creates triangles for which the smallest angle overall has the maximum value. The temperature of a point inside a triangle is then determined by the relative distance to its vertices. The Voronoi diagrams (solid lines in Figure 2) basically divides plane in regions that contain all the points closer to the known point than to any other known point. Temperature of a point inside a diagram is calculated based on the “stolen” territory from the original diagrams after a new region is formed for the point6. One of the drawbacks of this method is the generation of convex hull. Convex hull is an area bordered by the known points. The value for the grid point lying outside of this area cannot be calculated by interpolation and an extrapolation method has to be used. The methodology was explained for a 2D situation, but it can be upgraded into higher dimensions. For the purposes of our visualization, Delaunay tetrahedralization (triangulation in 3D space) and Voronoi 3D diagrams were implemented.

Figure 2. Delaunay triangulation (dashed lines) and Voronoi diagrams (solid lines) in a plane (X1-X9 points represent thermocouples and X point represents the grid point for which the value of temperature is calculated)8

Results and discussion Previously mentioned methods were applied to a case study of RHC reactor. Colour scale representing temperature was kept uniform for all visualized temperature profiles for easier comparison of achieved results. Figure 3 provides the simple overview of temperature profile inside the reactor using nearest neighbour interpolation and IDW method.

Figure 3. Comparison of using the nearest neighbor interpolation method (a) and IDW method (b – 3 thermocouples considered, c – all thermocouples considered) to calculate the temperature profile

(a) (b) (c)

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PETROCHEMICALS AND ORGANIC TECHNOLOGY

The temperature profile obtained by the nearest neighbour interpolation (Figure 3a) was not continuous and its use for process optimisation and temperature control system improvement was thus limited. Figures 3b and c demonstrate examples of temperature profiles obtained by IDW method for different numbers of considered thermocouples with the fixed value of exponent k in Equation 1 to be equal to one. The effect of value k on the obtained temperature profile was also studied and the results for the case study of all thermocouples considered are depicted in Figure 4. The use of IDW method significantly improved the profile continuity, although for higher numbers of considered thermocouples, the measured temperature extremes had tendency to disappear. This undesired phenomenon could be partially eliminated by increasing the value of k, but for higher values of k, the profile continuity was decreasing. The optimum values of k were found in the range of 3 to 4. For values of k greater than 20, the obtained temperature profile became similar to the temperature profile obtained by nearest neighbour interpolation. Temperature profiles obtained by basic interpolation methods were still not satisfactory and advanced interpolation techniques based on Delaunay tetrahedralization and Voronoi three-dimensional diagrams were applied. The results are depicted in Figure 5.

Figure 4. IDW method – impact of the value of the exponent k on the temperature profile considering all thermocouples – k = 2 (a), k = 4 (b) and k = 10 (c)

Figure 5. The temperature profile obtained using the principles of Delaunay tetrahedralization (a) and Voronoi 3D diagrams (b)

(a) (b) (c)

(a) (b)

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Figure 5a depicts the temperature profile calculated using the principles of Delaunay tetrahedralization and Figure 5b depicts the temperature profile obtained by implementation of Voronoi 3D diagrams. The temperature profiles obtained by both methods were continuous while preserving all the measured cold and hot spots in the reactor. Based on the process operation experience and discussions with process engineers, temperature profile visualization utilizing Voronoi 3D diagrams was selected for the implementation into reactor temperature control system and for further analysis of the reaction mixture behavior in the RHC reactors. The example of the final temperature profile using the developed visualization tool is shown in Figure 6.

Figure 6. 3D model example of the RHC reactor in the visualization tool developed in the MATLAB environment

Conclusion Goal of this study was to analyse interpolation techniques for the visualization of temperature profile in an RHC reactor utilizing measured data from day-to-day process operation and to create software solution suitable for implementation into the temperature control of the reactor. Several interpolation methods were tested to create continuous temperature profile preserving important measured temperature extremes such as hot spots in the catalyst bed. The nearest neighbor method offered an overview of the temperature profile but it was not suitable for further application because of the poor continuity. Use of the inverse distance weighting method seemed to be promising for temperature profile visualization with several issues to be considered, foremost the neglect of measured temperature extremes. This method yielded best results when considering all thermocouples and value of the exponent k was in the value range of 3 – 4. The best results were obtained in the case of Delaunay tetrahedralization and Voronoi 3D diagrams utilization recommended for the interpolation of scattered data. The interpolation method based on Voronoi 3D diagrams was selected for the implementation of the final software tool that was used for improved temperature control system of the analysed RHC reactors. Using the computational power of modern machines, many suitable ways to visualize temperature profile were found. Obtained results can be used not only to improve process control, but also to verify and enhance existing mathematical models and to improve process safety of the hydrocracking process. Real-time analysis of the reactor performance can contribute to avoid process hazards and emergency reactor shutdowns. Proper knowledge of temperature profiles inside the reactors can be also utilized in process optimization.

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Acknowledgment This work was supported by the Slovak Scientific Agency, Grant No. VEGA 1/0659/18 and the Slovak Research and Development Agency APP-14-0317.

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