【作者】 徐宁；

【导师】 楚纪正；

【作者基本信息】 北京化工大学 ， 控制科学与工程， 2012， 硕士

【摘要】 作为石油炼制加工的“龙头”，常减压蒸馏装置效益的提高对本装置、下游的二次和三次加工装置以及整个石化企业的效益有着十分重要的意义。企业的效益会受到装置运行状况的影响，而石化装置的稳态模拟能够为工艺改造提供依据，石化装置的操作优化能够为提升现有装置的效益提供方向，因此研究常压塔的稳态模拟及多目标优化研究意义重大。本文的主要内容如下：首先采用首先采用石油物系特征化用一系列假组分和确定的纯组分来表示原油，然后对各平衡级建立各特征化组分MESH方程，最后采用有效的求解策略求解非线性MESH大型方程组，并辅之以行之有效的校正策略，获得塔内各个重要工艺参数的分布，以及各个侧线产品、中段循环、塔顶油气产品的各项性质和状态。为了验证该模型的正确性，在流程模拟软件Aspen Plus上搭建同样的的稳态模型，并给出稳态模拟的结果和分析。其次在研究了优化算法中的GA、SA，结合GA和SA的优势和劣势的SAGA的基础上，针对自适应模拟退火遗传算法的弱点，提出引入跳跃基因算子的多目标模拟退火遗传算法，形成了改进后的ASAGA-JG算法。通过多种多目标算法性能度量指标和测试函数对改进的算法进行全方位的考察，验证ASAGA-JG的性能。最后将ASAGA-JG算法应用到常压塔装置的优化上，选取了适当的决策变量，优化目标为最大化利润和最小化能耗，约束条件为装置产品的质量指标和产品馏出率，在设置ASAGA-JG的算法参数之后，实现了基于ASAGA-JG的常压塔多目标优化。仿真结果表明常压塔装置当前的工况不是最优的，通过优化装置可以获得更高的利润和更小的能耗。该方法可靠高效，具备相当的应用价值。更多还原

【Abstract】 As the key unit in refinery fields, crude oil distillation unit (CDU) is thebasement of refinery enterprises. Its improvance in efficiency has huge impacton the efficiency of units downstream and the total profit of the entireenterprise. As we know, the profit of the entire enterprise is affected by therunning status of the units; in another word, it is affected by the stability andreliability of the control strategy. Aiming at enery saving, profit improving,and process optimization, the research of steady-state simulation andmulti-objective optimization of CDU has great meaning. The main work canbe summaried as follows：First of all, the author made a brief analysis on steady-state simulationand multi-objective optimization. And then, with rigid mechanism, the authorbuilded a steady-state model of CDU. For comparison with flow simulationsoftwares, the author also builded a steady-state model of the CDU with AspenPlus.Secondly, after the detailed research of simulated annealing algorithm,genetic algorithm, and simulated annealing genetic algorithm, and kept the advances and weaknesses of those algorithms in mind, proposed jumpinggenes adaption of adaptive simulated annealing genetic algorithm (ASAGA).And with many proven metrics and test problems, the author had tested theperformance of jumping genes adaption of ASAGA, the results showed thatjumping genes adaption of ASAGA is much better than ASAGA, and on sometest problems, it even better than NSGA-II and RJGGA.Thirdly, based on the rigid mechanism simulation of CDU, the authorselected the right objectives from the view of enterprise, suitable decisionvariables, and constrains. After finish constructing of multi-objective model,the new jumping genes adaption of ASAGA was applied into themulti-ogbjective optimization of CDU. It is observed that current plantoperation is sub-optimal and more profit can be realized for the same energycost using the obtained optimal operating conditions, which are under theconstraints of product quality and total distillate. The simulation resultsdemonstrate that the ASAGA-JG is able to generate non-dominated solutionswith a wide spread along the Pareto-optimal front and good address the issuesregarding convergence and diversity in multi-objective optimization.更多还原