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.     

Optimization of crude distillation system using aspen plus: Effect of binary feed selection on grass-root design

With an objective to supplement guidelines available as general rules of thumb for the grass-root design of crude distillation unit (CDU) using binary crude mixtures, this work presents the optimization of crude distillation unit using commercial Aspen Plus software. The crude distillation unit constituted a pre-flash tower (PF), an atmospheric distillation unit (ADU) and a vacuum distillation unit (VDU). Optimization model constituted a rigorous simulation model supplemented with suitable objective functions with and without product flow rate constraints. Three different feed stocks namely Bombay crude, Araby crude and Nigeria crude were considered in this work along with various binary combinations of these crudes. The objective function considered was profit function (subjected to maximization) for cases without product flow rate constraints and raw-materials and energy cost (subjected to minimization) for cases with product flow rate constraints. Parametric study pertaining to feed selection and composition has been conducted in this work to further benefit refinery planning and scheduling. Simulation study inferred that the product flow rate constraints sensitively affect atmospheric distillation column diameter and crude feed flow rate calculations. Based on all simulation studies, a generalized inference confirms that it is difficult to judge upon the quality of the solutions obtained as far as their global optimality is concerned.     

基于HYSYS和NSGA-Ⅱ的常压塔多目标优化

研究了炼油工业中常压塔单元的最优操作问题,通过流程模拟软件HYSYS模拟常压塔静态模型,并利用改进非支配排序遗传算法（elitist non-dominated sorting genetic algorithm, NSGA-Ⅱ）来求解效益-能耗多目标问题,从而得到一组最优操作条件Pareto解集,结果表明在保证各产品质量的前提下,常压塔全塔的经济效益还可以提高。     

基于特征选择的常减压装置模型及在计划优化中的应用

常减压装置将原油切割为不同中间产品,其作为炼油工艺的龙头装置,对炼油过程生产计划排产与效益提升至关重要。通过建立一种高精度且具有良好求解效率的常减压模型,用以求解模型关键指标实沸点（TBP）曲线,即综合考虑切割产品的实沸点（TBP）与原油TBP、流量、温度等变量影响,构建非线性方程组模型来表征输入输出间的关系;利用特征选择方法遴选相关变量（包括进料性质、相邻TBP及其二次项等）,并采用鲸鱼优化算法优化方程组系数。仿真结果表明,该多输出相互关系模型与已有文献工作相比,在兼顾求解效率基础上,常减压装置各蒸馏切割产品TBP曲线预测上有更高的精度,将此模型应用到炼厂计划优化中,与传统的悬摆切割模型对比,优化结果优于传统悬摆切割模型。     

Development of refinery scheduling system using mixed integer programming and expert system

This paper presents a hybrid refinery scheduling system combining mathematical programming model and expert system. Mixed-integer linear programming models for crude oil movement between units are merged into the expert system that is for qualitative issues concerning crude vessel unloading operations. The target problem ranging from the crude unloading to the crude charging to distillation towers is decomposed into several module problems for efficiency. Compared with existing scheduling approaches for oil movement, the proposed hybrid refinery scheduling system is very effective in dealing with timing decisions involving vessel unloading operations due to the advantages of an expert system. Since the proposed scheduling system can generate solutions so fast, it is expected to play a key role in the real processes. This paper is dedicated to Professor Wha Young Lee on the occasion of his retirement from Seoul National University.     

Energy saving in a crude distillation unit with a divided wall column

An energy-efficient crude distillation unit (CDU) with a divided wall column was introduced to evaluate its performance compared to the conventional CDU. The large energy demand of the CDU in the United States—equivalent to more than a half of biofuel produced—was reduced by applying a divided wall column to the unit also known as the energy-efficient distillation column. The divided wall column lowers mixing at feed tray and raises the thermodynamic efficiency of the CDU. The performance evaluation of the proposed unit indicates that the unit saves 37% of heat supply over the conventional unit and cooling by 17%. The economic analysis shows a 9% of investment saving and a 26% decrease in the utility cost from the proposed unit. The thermodynamic efficiency of the proposed CDU is improved by 8%. The modification of conventional CDU was minimal, suggesting an easy revamping of the current conventional CDUs.     

An Energy‐Efficient Crude Distillation Unit with a Prefractionator

An energy‐efficient crude distillation unit (CDU) was proposed, and its performance was evaluated and compared with that of a conventional CDU. The problem of the large energy demand associated with the single‐column operation of a conventional CDU was solved with a two‐column operation – a prefactionator and a main column – in the proposed CDU. The two‐column operation reduces feed‐tray mixing, and thus raises the thermodynamic efficiency of the CDU. The proposed unit has reduced heating and cooling duty compared with that of the conventional unit. The proposed unit also has fewer investment and utility costs. Vapor and liquid flow connections between the two columns are readily available by adjusting the difference in column operating pressure.     

炼油企业供应链管理中实沸点切割点的优化

20世纪90年代以来,国际石油和化工制造业面临新的挑战．企业要想提高竞争力,必须在产品成本、质量及新产品开发能力、生产灵活性以及用户的售后服务等方面取得优势．为此,应将企业整个生产过程放到供应链中去,使整个企业的原料供应→原料运输→仓储→生产制造→产品储存→产品运输→用户需求反馈等形成一个有机联系的系统（图1）．提高整个企业的生产和销售效率,就是提高供应链各环节的效率,对供应链进行动态优化,将所需数量和质量的产品,以最快的速度送到客户的手中．     

基于EGO算法的常压塔能量优化

常减压装置能量消耗约占炼厂总用能的25%～30%,在保证产品产量与质量的条件下,优化常减压蒸馏塔操作条件,可有效降低能耗.为了避免随机优化算法对常压塔机理模型进行操作优化时,存在计算资源消耗大、效率低的问题,文中采用基于代理模型的全局优化方法优化常压塔的余热回收过程,在优化迭代过程中用Kriging代理模型来代替耗时的精确模型评估.实验表明模型调用次数相较于粒子群优化算法减少了90%,优化时间减少了85%,实现了能量优化并且保证了侧线产品之间的分离精度.     

Agent-based supply chain management—2: a refinery application

The refinery business involves tasks that span several departments and process large amount of data. Among others, these include crude procurement, logistics and scheduling (storage, distillation units, etc.). Current refinery decision support systems (DSSs) fail to integrate all the decision-making processes of a refinery, to interface with other systems in place, to incorporate dynamic data from various sources and to assist different departments concurrently. In part 1 of this two-part paper, we proposed an agent-based framework for supply chain DSSs. Here, we demonstrate its application through a prototype DSS, called petroleum refinery integrated supply chain modeler and simulator or PRISMS, for crude procurement. PRISMS serves as a central DSS through which all processes of a refinery can be studied and enables integrated decisions with respect to the overall refinery business. In particular, PRISMS can be used to study the effects of internal policies of the refinery and its various departments. We illustrate this through three detailed ‘what-if’ studies that provide an insight into how the business responds to changes in policies, exogenous events and plant modifications.     

炼油企业全厂调度优化系统的设计与开发

生产调度优化对于炼油企业提高经济效益、增强市场响应速度有着重要的作用。本文设计并开发出一款图形化炼厂生产调度优化软件,采用MVC架构技术,实现了调度优化建模的图形化,可以方便组态炼油厂调度模型;将开源优化代码Coin-OR移植为调度优化软件的求解器,实现了求解器与图形化建模接口的连接;丰富的报表输出,让现场操作工可以各种形式获得调度优化结果;完善的内部模型数据管理和丰富的外部数据接口,包括原油性质指标库和原油评价数据库接口、成品油性质指标库等。仿真结果表明,该软件能够优化出符合炼厂生产实际的调度优化排产方案。     

Soft sensor for continuous product quality estimation (in crude distillation unit)

Due to the strict norm requirements of keeping products in crude refining units within specifications, laboratory testing and quality control of the products are necessary. Given this reason, virtual soft sensor for continuous quality estimation of light naphtha as the crude distillation unit (CDU) product was developed. Experimental data included available continuous measurements of CDU process streams (temperatures, pressures and flowrate) and laboratory analyses undertaken twice a day. The results are soft sensor models for light naphtha vapor pressure (RVP) estimation.Soft sensor models have been developed conducting multiple linear regression analysis and using neural network-based models such as LNN, MLP and RBF. Considering statistical and sensitivity analysis, the best results for both oils were obtained with MLP and RBF neural networks. The results show possible application of the soft sensor models for estimating light naphtha RVP as an alternative for laboratory testing.     

Optimization of a crude distillation unit using a combination of wavelet neural network and line-up competition algorithm

The modeling and optimization of an industrial-scale crude distil ation unit (CDU) are addressed. The main spec-ifications and base conditions of CDU are taken from a crude oil refinery in Wuhan, China. For modeling of a com-plicated CDU, an improved wavelet neural network (WNN) is presented to model the complicated CDU, in which novel parametric updating laws are developed to precisely capture the characteristics of CDU. To address CDU in an economically optimal manner, an economic optimization algorithm under prescribed constraints is presented. By using a combination of WNN-based optimization model and line-up competition algorithm (LCA), the supe-rior performance of the proposed approach is verified. Compared with the base operating condition, it is validat-ed that the increments of products including kerosene and diesel are up to 20％at least by increasing less than 5％duties of intermediate coolers such as second pump-around (PA2) and third pump-around (PA3).     

灵活应用LP模型提高炼油厂设计水平

炼油厂设计水平的高低首先取决于总加工流程的选择是否优化合理。本文利用PIMS软件提供的模块化和开放性结构的建模环境,结合炼油工艺特点,根据设计需要灵活地构建了各种LP模型,用于炼油厂实际总加工流程的优化设计中。同时重点介绍了其在原油配置、重油加工路线选择和新工艺评估方面的应用成果,结果表明其对提高炼油厂的整体设计水平具有重要指导意义。     

Overall efficiency evaluation of commercial distillation columns with valve and dualflow trays

The main objective of this work is to establish appropriated ways for estimating the overall efficiencies of industrial distillation columns with valve trays with downcomer and dualflow trays. The knowledge of efficiencies has fundamental importance in the design and performance evaluation of distillation columns. Searching in the literature, a tree of alternatives was identified to compose the tray efficiency model, depending on the mass transfer models, the liquid distribution and vapor flow models on the tray, the liquid entrainment model, the multicomponent mixture equilibrium model, the physical properties models, the height of froth on the tray model and the efficiency definition. In this work, different methods to predict the overall efficiency of distillation columns with valve and dualflow trays were composed and compared with data from three commercial distillation columns under different operating conditions. The models were inserted in the Aspen Plus 12.1 simulator, in Fortran language, together with tray geometrical data, fluid properties and operating data of the distillation columns. For each column, the best thermodynamic package was chosen by checking the temperature profile and overhead and bottom compositions obtained via simulation against the corresponding actual data of industrial columns. A modification in the fraction of holes evaluation that is jetting parameter of the Garcia's hydraulic model of dispersion above the tray was proposed. This modification produced better results than the original model to predict the fraction of holes that are jetting and in the efficiency of dualflow trays and similar results to Garcia model in the efficiency evaluation of valve trays. © 2010 American Institute of Chemical Engineers AIChE J, 2010     

Simultaneous optimization of heat-integrated crude oil distillation systems☆

Crude oil distil ation is important in refining industry. Operating variables of distil ation process have a critical ef-fect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum eco-nomic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum an-nual economic benefit of an existing crude oil distil ation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear program-ming problem and solved by stochastic algorithm of particle warm optimization.     

MODELING AND CONTROL OF A TEMPERATURE-BASED HIGH-PURITY DISTILLATION COLUMN*

Industrial distillation columns typically lack adequate on-line instrumentation required for implementing high performance, model-based control systems which depend on composition measurements. The typical practice is to base product quality control schemes instead on tray temperature measurements since these are usually available on-line. While this strategy has been applied with success on a wide variety of distillation columns, some special considerations may be necessary in dealing with high-purity columns. This paper presents results which address some of the key issues involved with the use of tray temperature measurements as surrogates for composition measurements, and with the development of appropriate input/output models for multi variable control of high-purity columns. For the purpose of illustration, we investigate the performance of several model predictive control schemes based on a linear model, a “high frequency” model, and a nonlinear temperature transformation, along with that of conventional multiloop PID control. Closed-loop control performances are compared for setpoint changes as well as for changes in unmeasurable load disturbances.     

Global optimization for scheduling refinery crude oil operations

In this work we present an outer-approximation algorithm to obtain the global optimum of a nonconvex mixed-integer nonlinear programming (MINLP) model that is used to represent the scheduling of crude oil movement at the front-end of a petroleum refinery. The model relies on a continuous time representation making use of transfer events. The proposed algorithm focuses on effectively solving a mixed-integer linear programming (MILP) relaxation of the nonconvex MINLP to obtain a rigorous lower bound (LB) on the global optimum. Cutting planes derived by spatially decomposing the network are added to the MILP relaxation of the original nonconvex MINLP in order to reduce the solution time for the MILP relaxation. The solution of this relaxation is used as a heuristic to obtain a feasible solution to the MINLP which serves as an upper bound (UB). The lower and upper bounds are made to converge to within a specified tolerance in the proposed outer-approximation algorithm. On applying the proposed technique to test examples, significant savings are realized in the computational effort required to obtain provably global optimal solutions.     

Continuous‐time modeling and global optimization approach for scheduling of crude oil operations

Scheduling of crude oil operations is a critical and complicated component of overall refinery operations, because crude oil costs account for about 80% of the refinery turnover. Moreover, blending with less expensive crudes can significantly increase profit margins. The mathematical modeling of blending different crudes in storage tanks results in many bilinear terms, which transforms the problem into a challenging, nonconvex, and mixed‐integer nonlinear programming (MINLP) optimization model. Two primary contributions have been made. First, the authors developed a novel unit‐specific event‐based continuous‐time MINLP formulation for this problem. Then they incorporated realistic operational features such as single buoy mooring (SBM), multiple jetties, multiparcel vessels, single‐parcel vessels, crude blending, brine settling, crude segregation, and multiple tanks feeding one crude distillation unit at one time and vice versa. In addition, 15 important volume‐based or weight‐based crude property indices are also considered. Second, they exploited recent advances in piecewise‐linear underestimation of bilinear terms within a branch‐and‐bound algorithm to globally optimize the MINLP problem. It is shown that the continuous‐time model results in substantially fewer bilinear terms. Several examples taken from the work of Li et al. are used to illustrate that (1) better solutions are obtained and (2) ε‐global optimality can be attained using the proposed branch‐and‐bound global optimization algorithm with piecewise‐linear underestimations of the bilinear terms. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Integrated crude selection and refinery optimization under uncertainty

Crude oil selection and procurement is the most important step in the refining process and impacts the profit margin of the refinery significantly. Due to uncertain quality of the crudes, conventional deterministic modeling and optimization methods are not suitable for refinery profitability enhancement. Therefore, a novel optimization scheme for crude oil procurement integrated with refinery operations in the face of uncertainties is presented. The decision process comprises two stages and is solved using a scenario‐based stochastic programming formulation. In Stage I, the optimal crude selections and purchase amounts are determined by maximizing the expected profit across all scenarios. In Stage II, the uncertainties are realized and optimal operations for the refinery are determined according to this realization. The resulting large‐scale mixed‐integer nonlinear programming formulation incorporates integer variables for crude selection and continuous variables for refinery operations, as well as bilinear terms for pooling processes. Nonconvex generalized Benders decomposition is used to solve this problem to obtain an global optimum efficiently. © 2015 American Institute of Chemical Engineers AIChE J, 62: 1038–1053, 2016