双管道原油处理短期生产计划的调度优化研究

The short-term scheduling problem of crude oil operations is one of the most difficult problems in scheduling an oil refinery. In the recent years, mathematical programming models are used to model the problem and solve by exact ways. But up to now, there is no effective technique and software tool for practical use because of the prohibitive computation. To solve this problem, our team studies the short-term scheduling problem of crude oil operations in a control theory perspective, and a two-layer hierarchical solution is proposed for it. At the upper level, a refining schedule is found, while a detailed schedule is obtained to realize the refining schedule at the lower level. So far, the upper level scheduling optimization problem was solved effectively by our team. But the lower level detailed schedule optimization problem needs to be solved urgently. This project tries to analyze the dynamic characteristics of crude oil transportation system with two pipelines, and builds the hybrid Petri net models. Based on these models, the detailed scheduling problem is transformed into an assignment problem in a control theory perspective, which can be solved by intelligent algorithms. Then, different intelligent algorithms are investigated for solving the detailed schedule at the lower level. Namely, we attempt to deal with the detailed schedule optimization problem at the lower level if the target refining schedule is known in advance. It will give great contribution for refinery enterprise automation.

原油处理短期生产计划问题是炼油短期生产计划中最困难的问题之一，目前通常用数学规划的方法进行建模、求解，但由于问题的极其复杂性，还没有有效的工具软件应用在实际生产过程中。本课题组经过长期积累，创造性地提出从混合系统控制角度，建立短期生产计划的两层求解框架，在上层求炼油生产计划以优化相关目标，在下层则求一个详细的短期计划以实现上层炼油计划。目前已成功解决了上层炼油计划的调度优化问题，但下层详细计划优化问题亟待解决。本项目拟通过分析双管道原油输送系统的动态特征，建立混合Petri网模型，从混合系统控制理论角度将问题转换为可用智能算法求解的资源指派问题，并用不同的智能算法对下层详细调度问题进行优化求解，解决在上层炼油计划已知的条件下，含高熔点原油运输的双管道原油输送系统的下层详细调度优化问题，为炼油企业的综合自动化实施做出有益的贡献。

炼油工业在国民经济中具有及其重要的地位，其短期生产计划优化可以带来巨大的经济效益和社会效益。但由于它的混合系统特性和解的可行性问题，启发式和智能算法无法直接应用。为此，本项目从混合系统控制的角度，首先对问题进行转换，使其转换为可以用智能算法求解的资源指派问题。最后再将多种智能算法应用于转化后的资源指派问题，并比较其优化效率。本项目主要研究了三个方面的问题：（1）提出了一种基于改进的骨干粒子群算法和II代非支配遗传算法协同进化的双种群算法，优化了供油罐使用成本、供油罐的切换成本、管道中原油混合成本以及供油罐罐底混合成本等多个目标。（2）首次将能耗优化作为原油处理下层详细调度的优化目标之一，以最合适的速率将原油从码头储油罐运送到厂区供油罐，而不是总是使用最大速率进行转运。节省了大量的能耗，意义重大。（3）将智能算法应用于含高熔点原油转运的双管道详细调度，提出了基于实数编码的双管道原油短期调度问题的一套编码和解码规则，能够减少问题中决策变量的个数，提高算法的求解效率。另外，还考虑了调度期间供油罐可能需要维护的情况，使得生成的调度方案更加符合实际的生产环境。除了目前已经投稿和还在撰写的论文外，到目前为止已发表署名该基金资助的科技论文共13篇，其中5篇发表在本领域国际上重要的SCI索引的期刊上，5篇发表在IEEE的国际会议上，另外3篇发表在中文核心期刊上。