Multisite facility network integration design and coordination: An application to the refining industry

This paper addresses the design and analysis of multisite integration and coordination strategies within a network of petroleum refineries using different crude combination alternatives. In addition, production capacity expansion requirements are also accounted for. The main feature of the paper is the development of a methodology for simultaneous analysis of process network integration alternatives in a multisite refining system through a mixed-integer linear program (MILP) with the overall objective of minimizing total annualized cost. The State Equipment Network (SEN) representation was used for modeling the network as it provides a consistent modeling strategy and proper handling of units that operate under different operating modes, which is common in the refining industry. The integrated network design specifically addresses intermediate material transfer between processing units at each site. The performance of the proposed model was tested on several industrial-scale examples to illustrate the economic potential and trade-offs involved in the optimization of the network. The use of mathematical programming models on an enterprise-wide scale to address strategic decisions considering various process integration alternatives yielded substantial benefits. These benefits not only materialize in terms of economic considerations, but also in terms of process flexibility and improvements in the understanding of the process interactions and systems limitations. Although the methodology was applied on a network of refineries, it can be readily extended to cover any network of continuous chemical processes.     

Integration strategies of hydrogen network in a refinery based on operational optimization of hydrotreating units

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries. It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries. An integration strategy of hydrogen network and an operational optimization model of hydrotreating (HDT) units are proposed based on the characteristics of reaction kinetics of HDT units. By solving the proposed model, the operating conditions of HDT units are optimized, and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization (HDS), hydrodenitrification (HDN) and aromatic hydrogenation (HDA) kinetics. An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model. Results show that HDS, HDN and HDA reactions are the major source of hydrogen consumption in the refinery. The total hydrogen consumption can be reduced by 18.9% by applying conventional hydrogen network optimization model. When the hydrogen network is optimized after the operational optimization of HDT units is performed, the hydrogen consumption is reduced by 28.2%. When the benefit of the fuel gas recovery is further considered, the total annual cost of hydrogen network can be reduced by 3.21×10₇ CNY·a_-1, decreased by 11.9%. Therefore, the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.     

炼油厂氢气网络建模与多目标优化(英文)

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.     

A novel graphical method for the integration of hydrogen distribution systems with purification reuse

Increase in refining demand and tighter environmental regulations have led to sharp increases in hydrogen consumption of oil refineries. Hydrogen conservation and effective use are of interest to refineries whose operations and profitability are constrained by hydrogen. Purification is widely used in hydrogen networks of refineries to reduce hydrogen production load. To minimize hydrogen utility consumption, it is necessary to optimize the hydrogen network with purification as a whole. In this paper, for hydrogen purification process, a triangle rule (which can be generalized to polygon rule) is proposed for graphical representation of its mass balance. The proposed procedure treats the product concentration and recovery rate of the purification process as adjustable parameters. An ensuing graphical method is developed for targeting the pinch point and minimum utility consumption of the hydrogen system with purification reuse. This graphical method can be used for any purification devices and in systems with any utility concentration. A refinery case is studied to demonstrate the optimization method.     

未来炼厂的发展趋势

阐述了在炼油工业面临严峻挑战的情况下,未来炼油厂向大型化,清洁化,智能化,一体化,轻质化和灵活化发展的趋势。     

炼油厂全厂工艺及热力管网的管道设计

随着国家经济的发展,对能源需求量的增大,炼油厂原油处理能力逐步增加,全厂工艺及热力管网的设计也日趋复杂。全厂工艺及热力管网设计是否合理直接关系到管理、操作、维护以及整个项目的投资和今后的发展。本文对炼油厂全厂工艺及热力管网管廊和管道的设计进行了阐述,希望对类似的设计具有一定的指导和借鉴作用。     

Heavy oil refining and transportation: effect on the feasibility of increasing domestic heavy oil production

As part of a programme to assess the feasibility of increasing domestic heavy oil production from US reservoirs, a study of the crude oil transportation system and petroleum refining industry has been initiated to determine their ability to accommodate additional domestic heavy oil. This paper summarizes refining trends and potential limitations in the production/transportation/refining network that may influence the expansion of domestic heavy oil production outside the current heavy oil producing areas. Although the number of refineries has decreased over the past decade, the remaining large refineries have been able to stabilize charge capacity and increase refinery throughput. A few refineries have been designed to economically process select heavy oils and obtain acceptable yields of products. However, refiners seek more light sweet crude oil and less sour or heavy crude to meet the requirements of clean fuels as mandated by the Clean Air Act Amendments of 1990. Transport of heavy oil poses significant problems in that there are limited heated pipelines, and transport of heavy oil to distant refineries adds to the cost of heavy oil production. Addition of significantly more heavy oil, either domestic or imported, will substantially reduce refinery efficiency and throughput affecting yields and margins. This will not change without significant investment in refinery modification to be able to process heavy oil.     

A machine learning framework for improving refinery production planning

We propose a framework that relies on machine learning techniques and statistical modeling to enhance industrial production planning. Supervised learning is employed to improve the production planning model, whereas unsupervised learning is used to achieve economic synchronization between the process control and production planning layers. Finally, an upgraded production planning decision-making structure is formulated where model uncertainty, the effect of process control/disturbances, and time correlation are considered. The proposed framework is implemented on an industry-relevant refinery model demonstrating that the performance of the framework is substantially better than established industrial production planning techniques.     

Coupling pinch analysis and rigorous process simulation for hydrogen networks with light hydrocarbon recovery

In refineries, some hydrogen-rich streams contain considerable light hydrocarbons that are important raw materials for the chemical industry. Integrating hydrogen networks with light hydrocarbon recovery can enhance the reuse of both hydrogen and light hydrocarbons. This work proposes an automated method for targeting hydrogen networks with light hydrocarbon recovery. A pinch-based algebraic method is improved to determine the minimum fresh hydrogen consumption and hydrogen sources fed into the light hydrocarbon recovery unit automatically. Rigorous process simulation is conducted to determine the mass and energy balances of the light hydrocarbon recovery process. The targeting procedures are developed through combination of the improved pinch method and rigorous process simulation. This hybrid method is realized by coupling the Matlab and Aspen HYSYS platforms. A refinery hydrogen network is analyzed to illustrate application of the proposed method. The integration of hydrogen network with light hydrocarbon recovery further reduces fresh hydrogen requirement by 463.0 m³·h^-1 and recovers liquefied petroleum gas and gasoline of 1711.5 kg·h^-1 and 643 kg·h^-1, respectively. A payback period of 9.2 months indicates that investment in light hydrocarbon recovery is economically attractive.     

RESEARCH NOTES Unified model of purification units in hydrogen networks

Purification processes are widely used in hydrogen networks of refineries to increase hydrogen reuse. In refineries, hydrogen purification techniques include hydrocarbon, hydrogen sulfide and CO removal units. In addition, light hydrocarbon recovery from the hydrogen source streams can also result in hydrogen purification. In order to simplify the superstructure and mathematical model of hydrogen network integration, the models of different purification processes are unified in this paper, including mass balance and the expressions for hydrogen recovery and impurity removal ratios, which are given for all the purification units in refineries. Based on the proposed unified model, a superstructure of hydrogen networks with purification processes is constructed.     

A decision tree based decomposition method for oil refinery scheduling

Refinery scheduling attracts increasing concerns in both academic and industrial communities in recent years. However, due to the complexity of refinery processes, little has been reported for success use in real world refineries. In academic studies, refinery scheduling is usually treated as an integrated, large-scale optimization problem, though such complex optimization problems are extremely difficult to solve. In this paper, we proposed a way to exploit the prior knowledge existing in refineries, and developed a decision making system to guide the scheduling process. For a real world fuel oil oriented refinery, ten adjusting process scales are predetermined. A C4.5 decision tree works based on the finished oil demand plan to classify the corresponding category (i.e. adjusting scale). Then, a specific sub-scheduling problem with respect to the determined adjusting scale is solved. The proposed strategy is demonstrated with a scheduling case originated from a real world refinery.     

一种混杂系统数据校正新方法

对于既包含连续生产过程又包含离散事件的混杂系统,尤其是对于带有生产方案切换的实际生产过程,通过在物料平衡模型中引入随机调度方程,从而构造出包含随机调度方程参数变量θ的新型协调模型,然后利用一种不确定模型的协调算法对此模型进行求解,最后,通过仿真研究证实了该方法的有效性和鲁棒性.     

A novel model for multi-plant mixed heavy crude oils refinery planning

In this paper, multi-refinery using the same heavy crude oils as raw materials is studied, while a new nonlinear model for mixed heavy crude distillation is proposed. In practical crude distillation operation, the distillate yield and product distribution of distillation units are different due to their various equipment and operating parameters, even the same ratio of raw materials is provided, so different process models for multi-refinery planning is therefore required. For process modeling, the relationships between total yields and mixing ratio of different refineries were determined, which is combined with process simulation using production data. Then, the yields and properties of crude distillation unit (CDU) fractions were calculated with the use of true boiling point (TBP) curves and property curves respectively when the initial cutting temperatures were given. Finally, in order to maximize the economic benefit of distillation, the optimal product distribution and the best mixing ratio of crude oil were calculated under the constraints of different properties of fractions. Comparing to previous models, the proposed model takes the influence of different refinery parameters on production process into account, while avoiding the complex process for determining the cutting points, which is considered more effi-cient and more accurate with respect to heavy crude refinery. Model was successfully verified by a case study, allowing a significant improvement of the refinery profit to be achieved.     

基于仿真的炼油厂罐区操作再调度策略

针对炼油厂操作过程中所存在的大量操作不确定性,提出了一种基于两层仿真系统的再调度方法保证了调度指令的稳定性。在下层模型中引入罐区操作的不确定干扰,并对初始优化方案进行仿真。上层仿真系统采用启发式寻优的方法,当下层干扰发生后得到保证组分和物料双重平衡的安全方案。基于此安全方案,通过固定混合整数线性优化模型中的二元变量并对方案的偏离进行惩罚从而缩小可行域快速得到局部优化解。以某炼厂罐区操作为例,验证了这一再调度策略的有效性。     

集成轻烃回收单元代理模型的氢气网络多目标优化

当前炼油企业氢气需求持续增长,导致炼厂成本及生产过程温室气体排放增加,炼油企业通过增设轻烃回收单元对氢气和轻烃组分进行回收利用,能有效缓解这一现状。因此,在氢气网络优化中有必要考虑轻烃回收单元。本研究提出了一种集成轻烃回收单元的氢气网络多目标数学规划模型,对轻烃回收单元采用代理模型建模方法,解决了直接嵌入严格机理模型可能导致的高计算成本问题,以总年度费用最小为优化目标,同时将系统的环境影响也纳入优化目标。实例计算表明,所提出的方法能够有效降低氢气网络的年度费用及温室气体排放,并揭示了集成轻烃回收单元的氢气网络经济性能与环境影响之间的权衡关系,为工业应用提供了一定的理论基础。     

常减压蒸馏装置节能途径探讨

由于常减压装置的能量消耗约占全厂能耗的20%～30%,一直都是炼油企业的用能大户,因此,我国各炼油厂对常减压装置进行的技术改造就显得十分重要。文章从新技术的使用、换热网络的优化等几个方面进行了较为详细的阐述,通过减少工艺用能来节省能量的消耗。     

Disaggregation-aggregation based model reduction for refinery-wide optimization

In this paper, reduced nonlinear refinery models are developed by generating and using input-output data from a process simulator. In particular, rigorous process models of continuous catalytic reformer (CCR) and naphtha splitter units are used for generating the data. To deal with complexity associated with large amounts of data, that is usually available in the refineries, a disaggregation-aggregation based approach is presented. The data is split (disaggregation) into smaller subsets and reduced artificial neural network (ANN) models are obtained for each of the subset. These ANN models are then combined (aggregation) to obtain an ANN model which represents all the data originally generated. The disaggregation step can be carried out within a parallel computing platform. Refinery optimization studies are carried out to demonstrate the applicability and the usefulness of the proposed model reduction approach.     

从催化干气中回收C2的工艺模拟与优化

乙烯是一种重要的化工原料,从催化干气中回收乙烯,能有效地降低我国炼油厂的生成成本,提高其经济效益。采用水合物-吸收耦合新工艺,对催化干气中C2组分进行回收。应用Aspen Custom Modeler模拟软件,对该工艺流程进行了设计和模拟优化。通过对乳液用量、理论板数、水含量、操作温度等参数进行优化,得到了不同乙烯回收率下的最优操作条件。     

Robustness analysis of chemical process systems based on complex network non-linear load capacity model

In the complex network of chemical process systems, if a node fails, it may trigger cascading failures and affect normal operation. To enhance the ability of chemical process systems to maintain normal operation after the cascading failure, this paper presents cascading failure modelling and robustness analysis of chemical process systems based on the complex network non-linear load capacity model. First, based on complex network theory, a complex network model of the chemical process is constructed; then, three cascading failure models are constructed using a combination of linear and non-linear load capacity models and initial load and initial residual capacity redistribution strategies; and finally, the nodes with the maximum node degree are deliberately attacked to analyze the robustness of the chemical process system in response to cascading failure. The case study shows that the proposed models are valid and feasible, and the robustness of the chemical process system is enhanced as the load and capacity parameters are increased. By reasonably setting the initial load and adjusting the model parameters, the robustness can be effectively improved, providing a theoretical reference for improving the robustness of the actual chemical process system in response to cascading failure.     

Analysis on Refinery System as a Complex Task-resource Network

the resources exchanged among tasks. Using the properties of node degree distribution, strength distribution and other weighted quantities, we demonstrate the heterogeneity of the network and point out the relation between structural characters of vertices and the functionality of corresponding tasks. The above phenomena indicate that the design requirements and principles of production process contribute to the heterogeneous features of the network. Besides, betweenness centrality of nodes can be used as an importance indicator to provide additional information for decision making. The correlations between structure and weighted properties are investigated to further address the influence brought by production schemes in system connectivity patterns. Cascading failures model is employed to analyze the robustness of the network when targeted attack happens. Two capacity assignment strategies are compared in order to improve the robustness of the network at certain cost. The refinery system displays more reliable behavior when the protecting strategy considers heterogeneous properties. This phenomenon further implies the structure-activity relationship of the refinery system and provides insightful suggestions for process system design. The results also indicate that robustness analysis is a promising application of methodologies from complex networks to process system engineering.