Predicting hydrotreater performance while co-processing vegetable oil
Catalyst performance prediction model based on test data assesses the impact of co-processing renewable feedstocks for optimal hydrotreater operations
Eelko Brevoord Catalyst Intelligence Tiago Vilela Avantium
M any refineries rely on pilot plant test data for select - ing catalysts, as this provides direct insight into their performance, facilitating selection of the best catalyst for increasing margins. Against this backdrop, pro - cessing renewable feedstocks can be a complex process due to the wide range and quality of feedstocks available. Therefore, Avantium developed a 16-reactor unit that can effectively test the impact of co-processing vegetable oil on the overall performance of catalysts. The selection of the right catalyst is crucial, given the diversity of feedstocks. In parallel, Catalyst Intelligence developed a catalyst per - formance prediction model (HydroScope) that translates pilot plant test data into commercial performance, enabling assessment of the impact of catalyst quality on overall prof - itability. Avantium partnered with Catalyst Intelligence to use its performance prediction model to optimise hydro - treating unit performance employing pilot plant test data and to enhance its catalyst testing services. The pilot plant test allows for the calculation of hydrodes - ulphurisation (HDS) activity, product selectivity, and inhibi - tion factors. The HydroScope model allows for assessing the impact of co-processing renewable feedstocks on cycle length, hydrogen consumption, and product yields. It is therefore recommended that test results be further
simulated in this hydroprocessing model. By doing so, an assessment of the most optimal unit conditions and their impact on cycle length can be made. While processing soybean oil, a portion of the oil is con - verted through the decarbonylation route, resulting in the formation of carbon monoxide (CO), which inhibits the HDS reaction. The CO can be removed by purging recycle gas, but this comes at the cost of valuable hydrogen. The impact of purging on cycle length can be calculated for each cata - lyst system, resulting in the selection of the most econom - ical solution. High-throughput catalyst testing Accurate catalyst evaluation is important in catalyst selec - tion, and increased product yields, energy efficiency, and overall product quality. High-throughput catalyst testing and small-scale reactors offer several advantages compared to larger reactor systems.¹ Using reactors of smaller scale to evaluate catalysts with renewable feedstocks presents a clear advantage; smaller volumes reduce the amount of feed required, avoiding the typical issues associated with obtaining large quantities such as handling, shipping, and storage (also for longer-term availability of reference feed material). Overall, small-scale parallel reactor systems like
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Figure 1 Mass balance for all feedstocks tested (colours varied by reactor) including water in gas measured in online GC
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PTQ Q3 2023
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