基于Aspen和信息分析法的常压塔的优化

Operational optimization of an industrial crude distillation unit using Aspen plus and information analysis

文章主要研究常压塔的操作优化问题,通过流程模拟软件Aspen模拟常压塔稳态模型,并采用了一种试验设计优化算法来对精馏塔进行操作优化。该算法主要通过人工神经网络来对目标过程建立元模型,同时运用信息分析法通过随机搜索,模糊聚类和最小信息自由能进行迭代计算来得到未来的试验数据,最终得到一组最优解。我们这里以常压塔全塔的经济效益为目标,运用该算法对其进行操作优化。结果表明在保证常压塔侧线产品质量和工艺要求的前提下,每小时可增加经济效益4485.90元,大大提高了全塔的效益。同时也证明了该算法的有效性和可行性。

This study provides insight into the problem of operational optimization of a simulated atmospheric distillation column. The simulated distillation process is based on a commercial software Aspen Plus, and a design of experiment （DOE） method is used to find the optimum operating conditions of the atmospheric distillation unit （ADU）. This constrained optimization procedure using artificial neural networks built meta-models for target processes. Information analysis based on random search, fuzzy c-mean clustering, and minimization of information free energy is performed iteratively in the procedure to suggest the location of future experiments and find the optimal value. In the operational optimization of the atmospheric distillation column, the performance index is taken as the negative increment of net profit. The result shows that the economic benefit of ADU could be increased. The increment of net profit is 4485.90 ￥/h. Significant profit increments show that operational optimization is meaningful and practical for the simulated atmospheric distillation unit（ADU）.