The residue hydrotreating process plays a significant role in the petroleum refining industry. In this process, modeling and simulation have critical importance for process development, control, and optimization. However, there is a lack of relevant reports of plant scale due to complexity in characterizing feedstock and determining reaction mechanisms. In this paper, reaction and fractionation models are constructed and simulated for a real-life industrial residue hydrotreating process based on Aspen HYSYS/Refining. Considering the heavier and inferior residue, analytical characterization is carried out for feedstock characterization based on laboratory analysis data. Moreover, two reactor models with parallel structures are proposed to implement the intricate reaction network, namely, a hydrocracker reactor and a plug flow reactor. The former simulates lighter petroleum hydrotreating based on the built-in reaction network. The latter emulates the conversion of a peculiar, heavier resin and asphaltene, using a six-lump model, which expands the scope of the feedstock and improves the accuracy of the model. To obtain a realistic simulation of fractionation, the database-based delumping method is adopted to model it with proper pseudo-components. The simulation results, including temperature rise, hydrogen consumption, temperature distribution, product yield, product properties, indicate that the model is capable of reflecting the realistic process accurately.

A fractionation system is an essential unit in the hydrocracking process. Its optimal operation is challenging because of the complexity in the structure of the distillation tower and composition of the stream. In addition, the seriesparallel structure between the distillation towers of different techniques aggravates the coupling and complexity of the hydrocracking fractionation system (HFS). This, in turn, increases the time complexity of the optimization problem. In this paper, a rigorous mechanism model of an actual HFS is first applied to describe the operating conditions of the HFS. Then, an improved state transition algorithm (STA) with a staged evaluation strategy is proposed to solve the above problem. To overcome problems caused by the series-parallel structure of HFS, the model is divided into multiple stages for evaluation by mechanism analysis. Furthermore, several typical convergence estimation criteria are introduced to reduce unnecessary model calculations. To solve time-consuming problems associated with HFS optimization, the adaptive change operator is used to improve the search function of the original algorithm and two performance criteria are presented to reduce the optimization time. The proposed algorithm is successfully applied to the operational parameter optimization problem of HFS with a multi-fractionator series-parallel structure. The experimental results indicated that the staged evaluation strategy improved the fast convergence probability of the HFS mechanism model and reduced unnecessary calculations, whereas the improved algorithm increased accuracy and significantly decreased optimization time.