【作者】 童凯亮；

【导师】 荣冈；

【作者基本信息】 浙江大学 ， 控制科学与工程， 2014， 博士

【摘要】 随着社会对能源需求的逐步增大,作为当今主要能源的石化燃料也面临着更高的供需要求。同时在石油日益短缺今天,生物燃料由于其环境友好,地域分布均衡,能值高等特点,成为了最有希望成为替代传统石油的新型能源。炼油厂的供应链优化在提升传统石化能源的整体生产效率,降低加工,运输和存储成本等各方面都起着极为重要的作用。与此同时,合理的利用现有炼油厂设施,设计合理的生物燃料供应链网络,可以有效的提升新能源的使用比率,从而进一步满足能源需求,促进社会发展。本文分别从提高炼油供应链和生物燃料供应链运作效率的角度上,对研究现状进行了具体分析,对炼油供应链计划优化,生物燃料供应链设计优化,以及两者供应链集成等问题进行了系统而深入的研究。本文的主要内容和创新点如下：1.提出了炼油厂供应链计划问题的条件风险价值模型,在最优化经济指标的同时控制风险,为炼油供应链计划问题中的不确定性处理提供了新思路。采用样本平均逼近的方法来确定最佳风险阈值,并且测试了结果的鲁棒性。在场景数量的选择上,采用统计的方法在精确性和计算效率之间做折中。同时,深入挖掘产率波动这一内在不确定性,提出了结合优化与仿真的迭代算法,在条件风险价值的随机规划的框架下,得出满意解。2.从炼油厂供应链的生产和配送的角度,分析了当前将炼油厂生产调度优化和管道调度优化分开考虑的不足与缺点,提出了生产调度和管道调度集成模型,从整体上优化生产调度,油品调和,管道调度与库存管理。相比传统顺序式的拉式和推式求解策略,该集成模型不仅能保证整体优化问题的可行性,而且能大幅降低整体成本。3.针对第三代高级碳氢生物燃料的供应链与现有炼油厂设备的关系,首次提出了碳氢生物燃料供应链集成已有炼油厂的设计优化模型。模型同时兼顾生物燃料供应链战略设计与战术计划优化两个因素,综合考虑了生物炼油厂的不同技术方案,加工规模的选择,与传统炼油厂集成策略的确定,以及生物质的分布性、季节性、易腐蚀性,需求的分布性和政府财政补贴等特点。采用模糊可能性规划方法对供应链设计优化模型中的不确定性进行分析优化,决策者可以根据个人偏好选择可能性,必然性和可信性当作评价指标。4.从最小化单位成本的角度,提出了高级碳氢生物燃料供应链集成已有炼油厂的混合整数分式规划模型。采用了两种特定算法对此优化问题进行求解。同时从最优解,容差,计算时间等方面比较了特定算法与通用的混合整数线性规划求解器在此优化问题上的差别。详细分析了以单位成本最小化与以总体成本最小化为目标的决策所造成的差别。提出了一个兼顾模型鲁棒性和经济性的鲁棒优化方法对供应链不确定性进行处理。5.首次提出了传统炼油厂和生物燃料集成供应链的长期设计和优化模型,分析两者供应链的互相协作与影响。采用装置级的炼厂计划模型代替简单的节点投入产出模型,提高了模型的分辨率。同时采用随机规划方法对长期设计计划过程中的不确定性进行分析控制。更多还原

【Abstract】 Enterprise optimization plays key role in both petroleum and biofuel supply chains. Supply chain optimization techniques could cooperate all the entities in petroleum refinery supply chain, and hence improve the production efficiency and reduce the overall cost. Moreover, biofuels have been proposed as part of the solution to climate change and our heavy dependence on fossil fuels. It is important to systematically design a sophisticated biofuel supply chain that takes the advantage of existing petroleum infrastructures. In this thesis, after reviewing recent researches on the supply chain optimization in both petroleum refinery supply chain and biofuel supply chain. We propose several novel models dealing with supply chain optimization problems under uncertainty. These models includes the petroleum supply chain tactical planning, biofuel supply chain strategy design, and the integrated supply chain design and planning. The details are listed as follows:1. A stochastic programming approach for an optimal refinery planning problem under uncertainties is proposed. The Conditional Value-at-Risk theory is used to deal with demand and yield uncertainties. Sample average approximation approach is employed to determine the suitable risk aversion value. A more accurate product yield distribution based upon Markov chain is introduced. The resulting problem with such endogenous uncertainty is solved using a heuristic iterative algorithm integrating stochastic programming and simulation framework. Furthermore, the scenario number in the stochastic programming model is determined by the statistical analysis, which is a compromise of model accuracy and problem size.2. From the view of production and distribution functions in petroleum supply chain, we present an integration model for refinery production scheduling and pipeline scheduling. A discrete time mixed-integer linear programming model is considered for scheduling problem of production and blending as the upstream of the refinery supply chain. A multi-product pipeline system using discrete mixed-integer linear programming formulation is adopted for products delivering. In this integrated model, production scheduling, product blending, pipeline scheduling, as well as the inventory management in both refinery and depots are considered in a holistic view. Compared with the traditional sequential solution strategy, the integrated model could guarantee the global feasibility and reduce the total cost.3. A multiperiod mixed-integer linear programming model is proposed to addresses the optimal design of an advanced hydrocarbon biofuel supply chain integrating with existing petroleum refineries. Three major insertion points from the biofuel supply chain to the petroleum refineries are investigated and analyzed. This model simultaneously optimizes the supply chain design, insertion point selection, and production planning, including diverse conversion pathway, technology, and insertion point selections, biomass seasonality, geographical diversity, biomass degradation, demand distribution and government incentives. In addition, a fuzzy possibilistic programming approach is applied to deal with uncertainties, where possibility, necessity and credibility measures are adopted according to the decision makers’ preference. Compared to the traditional biofuel supply chain, the advanced hydrocarbon biofuel supply chain integrating with existing petroleum refinery infrastructure significantly reduces the capital cost and total annualized cost.4. A mixed-integer linear fractional programming model with unit cost objective is proposed to address the design and planning of advanced hydrocarbon biofuel supply chain integrating with existing petroleum refineries. A robust optimization approach which tradeoffs the performance and conservatism is adopted to deal with the demand and supply uncertainty. Moreover, the unit cost objective makes the final products more cost-competitive. The resulting mixed-integer linear fractional programming model is solved by the tailored optimization algorithm. The results show that the preconversion to petroleum-upgrading pathway is more economical when applying the unit minimization objective.5. We address the problem of optimal design and strategic planning of the integrated biofuel and petroleum supply chain system in the presence of pricing and quantity uncertainties. To achieve a higher modeling resolution and improve the overall economic performance, we explicitly model equipment units and material streams in the retrofitted petroleum processes and propose a multi-period planning model to coordinate the various activities in the petroleum refineries. Furthermore, in order to develop an integrated supply chain that is reliable in the dynamic marketplace, we employ stochastic programming approach to optimize the expectation under a number of scenarios associated with biomass availability, fuel demand, crude-oil prices and technology evolution. Resutls show the market share of biofuels increases gradually due to the increasing crude oil price and biomass availability.更多还原