Prediction of Temperature Profiles for Catalytic Hydrotreating of Vegetable Oil with a Robust Dynamic Reactor Model

Abstract

Modeling and simulation of a three-phase commercialscale reactor for the catalytic hydrotreating of vegetable oil is reported to analyze the effect of reactor characteristics and mode of operation on product yields and temperature profiles along the catalytic bed length and time-on-stream. The model considers the variation of superficial gas velocity and effects of diffusion inside the catalytic particle to generate information in a more realistic large-scale environment. A series of simulations performed at different operating conditions show that the reaction heat released and hydrogen consumption are higher than those found for petroleum distillate hydrotreating, which enhances a sudden decrease in product yields. This information is vital to propose reactor design strategies, i.e., cooling systems, for a sharp temperature increase to optimize the performance of the entire process.

Key Factors to Use Existing Commercial Hydrotreating Plants for the Co-Hydrotreating of Vegetable Oil and Gas Oil

“…Because the deoxygenation reactions are highly exothermic, the modeling of the TBR considers the following energy balances under adiabatic nonisothermal conditions ,,− where a key parameter is the magnitude of the heat of reaction (Δ H R ) in eq . Theoretical considerations suggest that a high degree of exothermicity is expected due to high oxygen content (∼10 wt %) in vegetable oils (e.g., the Δ H R depends on the level of saturation of the fatty acids).…”

“…To control the reaction temperature, a temperature difference (ΔT) between the liquid phase throughout the catalyst bed length and feed mixture inlet temperature must be determined; in this way, the location and starting time of quench injections must also be adjusted. 75,76 In a quench zone, the effluent from the catalytic bed above is combined with the quench material before contacting it with the next catalytic bed. 74,77−79 The key idea is to create enough turbulence so that a uniform temperature may be established rapidly, and before redistribution, it is preferable to reach thermal equilibrium to reduce the fluctuations in temperature for the next catalyst bed.…”

“…To control the reaction temperature, a temperature difference (Δ T ) between the liquid phase throughout the catalyst bed length and feed mixture inlet temperature must be determined; in this way, the location and starting time of quench injections must also be adjusted. , …”

“…Because the deoxygenation reactions are highly exothermic, the modeling of the TBR considers the following energy balances under adiabatic nonisothermal conditions ,,− g as phase : 0.25em ε normalG ρ normalG C p normalG ∂ T normalG ∂ t = prefix− u normalG ρ normalG C p normalG ∂ T normalG ∂ z − h normalG normalL a normalL ( T G − T L ) l iquid phase : 0.25em ε normalL ρ normalL C p normalL ∂ T normalL ∂ t = prefix− u normalL ρ normalL C p normalL ∂ T normalL …”

Evaluation of Time-on-Stream Deactivation Models with Effectiveness Factors for Industrial Feedstock Hydrotreating in Bench-Scale Tests

“…This approach allows analyzing the influence of parameters, such as particle radius and temperature, on the effectiveness factor. 24,25 The transient characteristics of the effectiveness factor may also provide relevant data for reactions on porous catalysts. The usual assumption of steady states in the catalyst particles�classical effectiveness factors�is a particular case that corresponds to very slow or imperceptible changes in the medium where the catalyst particles are immersed.…”