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在石油化工领域中,分馏过程是流程模拟计算中重要的模块之一,在分馏过程模拟的主要输入参数中,塔盘效率无法直接获得,因此确定合适的塔盘效率是分馏模拟成功与否的关键因素,探索合适的方法确定板效率是精馏模拟的重要课题。本文在板效率确定方面,引入人工免疫动态克隆优化调节策略DCAS,与传统的智能优化算法相比,该算法的特点为:自动调整搜索空间及克隆规模;采用多尺度变异策略;有机结合全局与局部搜索能力。在实验中,通过建立分馏装置的机理模型,并采集装置的实际工况数据和各流股质量组成的分析数据,对所采集的数据依据稳态过程的物料守恒方程等进行剔除和校正处理,采用校正后的工况数据作为模型的输入,分别用经验法、遗传算法GA及人工免疫动态调整策略DCAS确定分馏装置的塔板效率,使模型与实际装置达到最大程度的吻合。研究结果表明,用DCAS确定的塔板效率,能够使分馏塔的关键塔板温度分布及分馏塔塔顶、塔釜主要产品的产出与实际吻合得最好,表明用DCAS搜索的塔板效率建立的分馏塔模型能够较好地描述实际分馏塔的生产过程,可以用来指导分馏装置的过程模拟及优化操作。
In the field of petrochemicals, fractionation is one of the most important modules in the process simulation. Since the efficiency of the trays can not be obtained directly from the main input parameters simulated in the fractionation process, the appropriate tray efficiency is determined by the success of the fractionation simulation The key factor to explore the appropriate method to determine the plate efficiency is an important issue of distillation simulation. In the aspect of board efficiency, DCAS, which is a dynamic clonal optimization and adjustment strategy based on artificial immunity, is introduced. Compared with the traditional intelligent optimization algorithm, this algorithm has the following features: automatic adjustment of search space and cloning scale; multi-scale mutation strategy; organic combination of global and Local search capabilities. In the experiment, by setting up the mechanism model of fractionation device and collecting the actual working condition data of the device and the analysis data of the quality of each stream, the collected data are removed and corrected according to the material conservation equation of the steady state process, Using the corrected working data as the input of the model, the plate efficiency of the fractionator was determined by empirical method, genetic algorithm GA and artificial immune dynamic adjustment strategy DCAS, respectively, which maximized the agreement between the model and the actual device. The results show that the efficiency of the tray determined by DCAS can make the temperature distribution of the key tray of the fractionation tower and the output of the main products of the top of the fractionator and the bottom of the distillation column be the best and the actual results show that the tray efficiency The established fractionation tower model can describe the actual distillation tower production process better and can be used to guide the process simulation and optimization of the fractionation plant.