A general framework for incorporating molecular modelling into overall refinery optimisation

A systematic methodology is presented for refinery modelling and optimisation on the basis of much more detail molecular information than conventional lumped methods. The novelty of this work is to incorporate models based on microscopic understanding into optimisation to achieve macroscopic improvement. A molecular matrix based on homologous series of hydrocarbon compounds (B. Peng, Ph.D. Thesis, UMIST, 1999, pp. 22–41) is used to characterise refining streams. A transformation method is developed for obtaining molecular compositions from stream bulk properties. Molecular models are then built for several processes. Molecular modelling and optimisation are finally integrated into an overall refinery optimisation framework. Results show that molecular information can provide much better understanding and new insights into refining operation. Consequently optimisation based on molecular modelling can greatly improve total profit while making quality products satisfying environmental regulations.     

对优化加工劣质原油前期设计的探讨

炼油行业根据原油的一般性质,把原油大致分为优质、中质和劣质三大类.劣质原油除了(.)API值小、硫含量大、总酸值高外,还呈现如下特点:常压拔出率低,常压重油产率(或减压渣油产率)高,黏度大,且杂质含量高,主要表现为硫含量、重金属(Ni+V)含量高,残炭值高.以加工能力为20Mt/a Merey-16原油的燃料型炼油厂为例,阐明优化加工劣质原油前期设计的全过程,即在建立LP模型基础上,利用相关软件对全厂总加工流程进行优化.因为原油性质太差,需要在其公用工程、特别是公用工程岛的优化-评价后,才能得出最终结果.当利用石油焦作为IGCC原料时,只有选用热回收方案,才能实现余热回收量、超高压水蒸气产量、酸性气回收量最大化,从而实现水蒸气能量的全过程、逐级优化利用;实现硫磺、CO2高回收率;在保障本装置低碳化的同时,使全炼油厂最大限度地节能减排.     

Thermodynamic simulation and evaluation of sugar refinery evaporators using a steady state modelling approach

In a sugar refinery, the juice is concentrated through evaporation, with the objective of concentrating the juice to syrup as rapidly as possible. Because the heat of vaporization of water is relatively high, the evaporation process can be highly energy intensive, and therefore the economical use of steam is important in the refinery. This paper reports on the development of a simulation model for the evaporation sections of two Mauritian sugar refineries.The first objective was to use the simulation model to carry out an energy balance over the evaporators in order to assess the economy of steam usage over the refinery.The second objective was to examine to what extent a fundamental steady state model, based on thermodynamics (not kinetics) was capable of predicting the material and energy flows in two operating sugar refineries and thereby to evaluate the applicability of the modelling framework.The simulation model was validated using historical data as well as data from the plant DCS system. The simulation results generally correlated well with the measured values, except for one of the evaporators on one refinery. Some suggestions were made as to the cause of the discrepancy. On balance, it was found that both refineries are extremely efficient in terms of steam and equipment usage and that there is not much scope for energy optimisation within the present configuration – nor for much spare steam capacity for an additional refinery.It was also shown that steady state process simulation, using thermodynamic models, can generate a very useful representation of a working refinery. Besides being able to use the model to “benchmark” the operation and thus evaluate its performance as a whole as well as across individual units, it could also be used to evaluate refinery performance across refineries, nationally as well as globally.     

Modelling and allocation of CO2 emissions in a multiproduct industry: The case of oil refining

As oil refining is a multiproduct industrial activity, there are innumerable ways to allocate a refinery’s CO₂ emissions among the various refined products. The linear-programming models used to manage refineries may serve to compute the marginal contribution of each finished product to the CO₂ emissions of the refinery. We show that, under some conditions, this marginal contribution is a relevant means of allocating all the refinery’s CO₂ emissions. The application of this allocation rule leads to interesting results which can be used in a well-to-wheel life cycle assessment. In fact, this allocation rule holds rigorously if the demand equations are the only binding constraints with a non-zero right-hand side coefficient. This is certainly not the case for short-run models with fixed capacity of processing units. To extend the application field of our approach, we therefore suggest three distinct solutions, inspired by economic theory: applying the Aumann–Shapley cost-sharing method, or adapting the Ramsey pricing-formula, or using proportionally-adjusted marginal contributions. A numerical application to a simplified refining model is presented.     

Process simulation and CFD calculations for the development of an innovative baled biomass-fired combustion chamber

This present work shows that the joint application of process simulation and computational fluid dynamics (CFD) is a helpful tool for the design and optimisation of complex and innovative concepts in chemical engineering practice. The application of these tools to the presented concept of a baled biomass-fired combustion chamber enables the optimisation of operation parameters such as the flue gas recirculation rate and excess air supply. Moreover numerous variations of the detailed engineering of the involved apparatuses can be simulated before realisation. The major goals comprise the maximisation of the thermal efficiency and the reduction of gaseous and particulate matter emissions. To meet these goals it is rather important to have available validated mathematical models with sharpened model parameters. Therefore the presented model approaches have been validated and refined using results from extensive combustion experiments conducted at an existing 2 MW pilot plant. Several modelling approaches are presented that especially focus on the treatment of the heterogeneous combustion and prediction of gaseous emissions such as carbon monoxide and nitrogen oxide. With validated models on a sound physical basis, process simulation and computational fluid dynamics enable a significant reduction of the development costs and the time-to-market of innovative chemical engineering concepts.     

Challenges and technological opportunities for the oil refining industry: A Brazilian refinery case

The worldwide oil refining industry currently faces strong challenges related to uncertainties about future feedstock and characteristics of oil products. These challenges favor two main strategies for the sector: the first strategy is increasing refinery complexity and versatility; the second is integrating the refining and petrochemical industries, adding value to the crude oil while guaranteeing market share to premium oil products. Both strategies aim at increasing production of highly specified oil products, simultaneously reducing the environmental impacts of the refining industry. This paper analyses the case of a Brazilian refinery, Gabriel Passos Refinery (REGAP), by proposing additional investments to alter and/or expand its current production scheme. All the proposed options present relatively low investment rates of return. However, investments in a hydrocracking based configuration with a gasification unit providing hydrogen and power can further improve the operational profitability, due to reduced natural gas consumption.     

Parameter characterization of HTPEMFC using numerical simulation and genetic algorithms

This paper develops a novel approach to the parameterisation of high temperature exchange membrane fuel cells (HTPEMFC) with limited and non-invasive measurements. The proposed method allows an effective identification of electrochemical parameters for three-dimensional fuel cell models by combining computational simulation tools and genetic algorithms. To avoid each evaluation undertaken by the optimisation method involving a complete computational simulation of the 3D model, a strategy has been designed that, thanks to an iterative process, makes it possible to decouple the fluid dynamic resolution from the electrochemistry one.Two electrochemical models have been incorporated into these tools to describe the behaviour of the catalyst layer, Butler-Volmer and spherical aggregate. For each one, a case study has been carried out to validate the results by comparing them with empirical data in the first model and with data generated by numerical simulation in the second. Results show that, from a set of measured operating conditions, it is possible to identify a unique set of electrochemical parameters that fits the 3D model to the target polarisation curve. The extension of this framework can be used to systematically estimate any model parameter in order to reduce the uncertainty in 3D simulation predictions.     

Modeling and simulation of absorption–desorption cyclic processes for hydrogen storage-compression using metal hydrides

This work is aimed to develop and analyze reduced and simplified lumped models of cyclic processes for hydrogen storage and thermal compression using metal hydrides. Rigorous models involve several thousands of variables whereas reduced models we are interested in involve only several tens of variables. The models here presented reproduce the main dynamic behavior of rigorous models and experimental data found in the literature. Furthermore, the main tradeoffs arisen in process design are well described with these models, which is always an objective of optimal process design.In the first part of the work, a simplified lumped model is developed and validated by comparing the simulations outcome with numerical results and experimental measurements obtained from the literature for absorption and desorption individual processes. Our model is then used to simulate the process behavior using real parameters and constraints required by continuous recovery and compression systems such as those found in the metal treatment industry. The simulation results are used to improve the process performance by adjusting some key parameters of the system. These results are also used to perform a sensitivity analysis, i.e. evaluate the storage/compression system behavior when introducing variations to parameters such as operating conditions, reactor design, and material properties.Finally, we further reduce the model by considering that the inlet and outlet hydrogen flow is approximately constant. This particular specification is usually required by continuous processes in the metal treatment industry where hydrogen flow must remain constant. This requirement allows considering reaction rate as a constant. The constant reaction rate constraint allows integrating the ordinary differential equations; hence the system no longer has differential and algebraic equations but just algebraic equations. As a consequence of the simplification, the number of equations to be solved is reduced from over 15,000 to less than 50, maintaining an excellent match in the results.     

Hydrogen distribution in the refinery using mathematical modeling

The increased requirement of hydrogen in the refinery is fulfilled by proper distribution of available hydrogen in the refinery, using additional hydrogen production system and by importing. Amongst these options first one is cost effective as no addition source is required. Thus, the present paper deals with optimum distribution of hydrogen. For this purpose mathematical models are developed based on pressure constraints, source and sinks constraints, compressor flow rate recycle and purity constraints, flow combinations, hydrogen consumption, operating cost, capital cost, payback period etc. The model is developed in stages to show the improvements.Two case studies, Cases A and B, are considered in this paper and for these linear programming (LP), nonlinear programming (NLP), mixed-integer linear programming (MILP) and mixed-integer nonlinear programming (MINLP) models are developed. The results predicted using these models are compared to select the best network. The optimized network for Case A consumes 20.9% less hydrogen, whereas, for Case B it is reduced by 32.3%.     

东南亚地区炼油行业概况

东南亚地区的炼油行业近年来发展很快.目前新加坡已拥有67.85Mt/a的炼油能力,是世界三大炼油中心之一,也是亚洲地区的主要石油产品输出国.印尼当前拥有9家炼油厂,炼油能力为52.85Mt/a,其炼油产品主要供应国内市场,但只能满足国内消费需求的约70％.马来西亚共有6座炼油厂,总加工能力约为29.55Mt/a,马来西亚国家石油公司Petronas是该国最大的石油公司,其加工能力占马来西亚总炼油能力的50％左右;此外,在石油价格居高不下的情况下,马来西亚加大了棕榈油提炼燃油产业化步伐,2012年该国的生物柴油产能有望超过1.0Mt.泰国目前共有7家炼油厂,总炼油能力为51.85Mt/a,并且该国也在大力发展生物燃料生产.菲律宾目前实际总炼油能力为15Mt/a,Petron公司是该国最大的石油炼制和销售企业,能满足国内40％的燃料需求.文莱探明原油储量为190Mt,有一座加工能力为5Mt/a的炼油厂,正在筹建一座能力为10Mt/a的炼油厂.越南探明石油储量为82.19Mt,近期石油日产量为55kt,目前只有一座加工能力为6.5Mt/a的炼油厂,正在筹建另外两座炼油厂.缅甸共有3座炼油厂,总炼油能力为2.55Mt/a.老挝、柬埔寨和东帝汶等其他国家正在积极开展油田勘探、开采和炼厂筹建工作.     

世界炼油工业二氧化碳减排进展

《京都议定书》的生效和哥本哈根全球气候峰会的召开对高能耗高排放的炼油工业的发展产生了很大影响．环保问题尤其是二氧化碳排放将成为决定炼厂能否可持续发展的重要因素。炼厂中二氧化碳排放源比较分散．提供热能、蒸汽和电力的过程会大量排放二氧化碳,制氢过程也是二氧化碳的主要来源。加热炉是炼厂二氧化碳最大的排放源,而催化裂化、制氢等是炼厂主要的高排放装置。不同燃料对炼厂二氧化碳排放的影响也有很大差别。其中排放量最多的是焦炭,最少的是天然气。此外原油质量和产品分布也会影响二氧化碳排放。为保证长期持续的竞争力。国际大石油公司已经开始积极制定减排战略,并在炼厂中采取措施应对二氧化碳排放。这些措施包括提高装置能效、投资可再生能源和开展CCS项目等。我国对CCS技术的发展给予了高度重视。我国炼油工业应积极转变经济增长方式,加快开发自身减排潜力,统筹制定二氧化碳减排战略,积极主动应对温室气体减排压力。     

Hedging downside risk of oil refineries: A vine copula approach

The financial health of an oil refinery greatly depends on its refining margin or the difference between the prices of its refined products (typically, gasoline and heating oil) and the cost of crude oil. The refinery may hedge against the downside risk of unfavorable price movements using crude oil, gasoline, and heating oil futures. This paper examines the use of a vine copula approach to estimate multiproduct hedge ratios that minimize the downside risk of the refinery. The advantage of the vine copula approach is that it allows us to capture important characteristics of petroleum price changes, including skewness and fat-tailedness in the marginal distributions of individual price change series as well as heterogeneous (tail) dependence patterns between different pairs of price changes. The out-of-sample hedging effectiveness of two popular classes of vine copula models – canonical (C-) and drawable (D-) vine copula models – are evaluated and compared with that of the widely used nonparametric method and three standard multivariate copula models. The empirical results reveal that the D-vine copula model is a good and safe choice in managing the downside risk of the refinery.     

An Exact-Steady-state Adaptive Chemistry method for combustion simulations: Combining the efficiency of reduced models and the accuracy of the full model

Many reduced-model methods have been developed to alleviate the computational expense of simulating chemically reacting flows with detailed kinetics. However, it is still impossible to determine exactly the loss in accuracy relative to the full model when reduced kinetic models are used for predicting quantities of interest (typically state variables). Ideally, one wishes to obtain the predictions of the full chemistry model at the fast speed of the simplified model(s). This paper describes a technique for achieving this goal for steady-state simulations. The new method, called Exact-Steady-state Adaptive Chemistry (ESAC), performs multiple fast reduced-model simulations of the steady-state problem, each time refining the accuracy of the solution by using increasingly accurate reduced models. Smaller (less accurate, but faster) reduced models are used when the simulation is far from (the full-model) steady-state; and more accurate (larger, slower) models are used as the simulation approaches the final steady-state solution. The simulation is completed by applying the trusted full kinetic model, guaranteeing the accuracy of the steady-state solution obtained using ESAC. We have developed a basic algorithm that applies this method and we present results from 2-D CFD simulations of steady-state methane and ethylene flames. ESAC simulations yielded the full-model solution (as guaranteed by the method) and were generally a factor of 3–4 times faster than the equivalent standard full-model-everywhere simulations. Future refinement of the basic implementations described here can further increase the speedup obtained when using ESAC. In applications where computational time rather than computer memory availability is the limiting factor, this technique enables efficient computation of the steady-state predicted by the full, detailed chemical kinetics model.     

Optimisation for forced cool-down processes with minimum cooling fluid mass

The analysis and optimisation of forced cool-down processes for minimising cooling fluid mass have been repeated. A physical model of forced cool-down process, which is closer to practical processes, is established by revising the original model with the consideration that the temperature of the cooling fluid depends not only on time, but also on the position while in contact with the cooled body. Two mathematical models, an exact model and an approximate model, of the optimisation problem for minimising the cooling fluid mass are established based on the revised physical model. Optimal control theory is applied to obtain the optimal configuration of the forced cool-down process for minimising cooling fluid mass with a fixed time interval. Numerical examples for the optimal configurations in the case of the revised model are provided, and the obtained results are compared with those obtained on the basis of the original model of the forced cool-down process.     

Structural analysis and optimization of a tethered swept wing for airborne wind energy generation

In this paper, we present an aero‐structural model of a tethered swept wing for airborne wind energy generation. The carbon composite wing has neither fuselage nor actuated aerodynamic control surfaces and is controlled entirely from the ground using three separate tethers. The computational model is efficient enough to be used for weight optimisation at the initial design stage. The main load‐bearing wing component is a nontypical “D”‐shaped wing‐box, which is represented as a slender carbon composite shell and further idealised as a stack of two‐dimensional cross section models arranged along an anisotropic one‐dimensional beam model. This reduced 2+1D finite element model is then combined with a nonlinear vortex step method that determines the aerodynamic load. A bridle model is utilised to calculate the individual forces as a function of the aerodynamic load in the bridle lines that connect the main tether to the wing. The entire computational model is used to explore the influence of the bride on the D‐box structure. Considering a reference D‐box design along with a reference aerodynamic load case, the structural response is analysed for typical bridle configurations. Subsequently, an optimisation of the internal geometry and laminate fibre orientations is carried out using the structural computation models, for a fixed aerodynamic and bridle configuration. Aiming at a minimal weight of the wing structure, we find that for the typical load case of the system, an overall weight savings of approximately 20% can be achieved compared with the initial reference design.     

Simulation-based modeling and optimization for refinery hydrogen network integration with light hydrocarbon recovery

Purge gases from hydrocrackers and hydrotreaters and refinery off-gases are important hydrogen sources. Some of these hydrogen sources are also rich in light hydrocarbons that are valuable energy resources and chemical materials. In this work, a systematic method is proposed to integrate hydrogen networks considering light hydrocarbon recovery. This work first develops a hydrogen network superstructure with light hydrocarbon recovery. Aspen HYSYS is employed for rigorous process and thermodynamic modeling of the light hydrocarbon recovery process, and a simulation-optimization model is then developed. To solve the simulation-optimization model efficiently, the genetic algorithm is used as the global solver to determine the feed to light hydrocarbon recovery unit, and the linprog and fmincon solvers are combined to determine the optimal hydrogen network design. The application and effectiveness of the proposed method is validated through a case study. The results show that fresh hydrogen consumption decreases by 13% and the total annualized cost reduces to 72% because of light hydrocarbon recovery. This method could provide useful guides for the management of hydrogen and light hydrocarbons in refineries.     

Optimal flowsheeting synthesis for power station design considering overall integration

This paper presents a novel methodology for flowsheet synthesis of power plants. In this new method, thermodynamic analysis and mathematical programming are combined by taking advantage of these two methods. A level-by-level approach is adopted in this method in order to reduce the mathematical complexity and computational difficulty of a design problem. More importantly, this approach provides good opportunities for user interaction. In the first level of flowsheet synthesis, an initial superstructure is constructed which embeds several possible design options. This superstructure is formulated to give a so-called master model, in which major subsystems of a plant are modelled in relatively simple models. Major aspects and key variables are taken into account in the master model and optimisation of this model gives an initial flowsheet. Following that, thermodynamic analysis is applied to identify relevant structural modification options to the flowsheet. These options are added to the master model superstructure, which is optimised to get an improved design. This loop of optimisation and analysis is carried out until no desirable improvement can be made. The results from the above design process provide the scope and requirements for the conceptual design of the subsystems. If it is impractical for a conceptual design to satisfy the requirements derived from the overall plant context, an updating mechanism is provided to either introduce additional constraints or alternative practical designs to the master model. The master model is then optimised again and a new conceptual design is carried out. This optimisation and design process terminates when the conceptual design can meet the design requirements determined by the master model. As a result of applying this method, an optimal design can be achieved with confidence even for large industrial problems.     

Review of models for predicting the cycling performance of lithium ion batteries

A rigorous pseudo two-dimensional model to simulate the cycling performance of a lithium ion cell is compared with two simplified models. The advantage of using simplified models is illustrated and their limitations are discussed. It is shown that for 1C or less discharge rates a simple ordinary differential equation (ODE) model can be used to predict accurately the potential as a function of time. For rates higher than 1C, simplifications to the rigorous model are suggested that reduce the solution time for the model.