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.     

Consequence Identification for Maloperation in Batch Process

Batch processes are important in chemical industry, in which operators usually play a major role and hazards may arise by their inadvertent acts. In this paper, based on hazard and operability study and concept of qualitative simulation, an automatic method for adverse consequence identification for potential maloperation is proposed. The qualitative model for production process is expressed by a novel directed graph. Possible operation deviations from normal operating procedure are identified systematically by using a group of guidewords. The proposed algorithm is used for qualitative simulation of batch processes to identify the effects of maloperations. The method is illustrated with a simple batch process and a batch reaction process. The results show that batch processes can be simulated qualitatively and hazards can be identified for operating procedures including maloperations. After analysis for possible plant maloperations, some measures can be taken to avoid maloperations or reduce losses resulted from maloperations.     

Production of glycerol carbonate via reactive distillation and extractive distillation:An experimental study☆

A process for the production of glycerol carbonate (GC) is proposed with the transesterification of glycerol (GL) and dimethyl carbonate (DMC) with CaO as catalyst by reactive distil ation and extractive distil ation. The perfor-mance of solvents in separating DMC-methanol azeotrope and the effects of operation parameters on the reactive distillation process are investigated experimental y. The results indicate that both the GL conversion and GC yield increase with the DMC/GL molar ratio, reflux ratio, final temperature of tower bottom, and CaO/GL molar ratio and decrease as the recycle number of CaO increases. The calcium concentration in the residual reaction mixture also decreases remarkably as the DMC/GL molar ratio increases. At DMC/GL molar ratio 4.0, reflux ratio 1.0, final temperature of tower bottom 358 K, and CaO/GL molar ratio 0.05, both the GL conversion and GC yield can reach above 99.0%, and the mass concentration of calcium in the product is less than 0.08%.     

The development of Fructus corni quality standard considering the effects of processing

The quality standards for Fructus Comi have been established based on the effects of the manufacturing processes.Three critical process parameters(CPPs) of extraction,filtration,and concentration to prepare Fructus Comi concentrate were identified by Plackett-Burman design with a single batch of Fructus Corni,which were heating medium temperature,extraction time,and water addition.Morroniside yield,loganin yield,and dry matter yield were process critical quality attributes(CQAs).CPPs arranged with a Box-Behnken design were applied to treat different batches of Fructus Comi After constructing a model that included CPPs,material propertie s,and process CQAs,loganin content was found to be the critical material attribute(CMA).The design space was calculated with a probability method.According to the limits of process CQAs,the minimum content of loganin in Fructus Corni was calculated with an error propagation method,which was 6.92 mg·g~(-1).When the content of loganin in Fructus Corni reaches up to 6.92 mg·g~(-1), the material is considered high-quality and is most suitable for the process.High-quality material can be used for production of Fructus Comi concentrate.This method can also be used to set material quality standards for other Chinese medicines.     

基于时段过渡分析的多时段间歇过程质量预测(英文)

Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them consider phase transitions, though they exit widely in batch processes and have non-ignorable impacts on product qualities. In the present work, a phase-based partial least squares (PLS) method utilizing transition information is proposed to give both online and offline quality predictions. First, batch processes are divided into several phases using regression parameters other than prior process knowledge. Then both steady phases and transitions which have great influences on qualities are identified as critical-to-quality phases using statistical methods. Finally, based on the analysis of different characteristics of transitions and steady phases, an integrated algorithm is developed for quality prediction. The application to an injection molding process shows the effectiveness of the proposed algorithm in comparison with the traditional MPLS method and the phase-based PLS method.     

Simulation of Fuel Ethanol Production from Lignocellulosic Biomass

Models for hydrolysis, fermentation and concentration process, production and utilization of biogas as well as lignin gasification are developed to calculate the heat demand of ethanol production process and the amounts of heat and power generated from residues and wastewater of the process. For the energy analysis, all relevant information about the process streams, physical properties, and mass and energy balances are considered. Energy integration is investigated for establishing a network of facilities for heat and power generation from wastewater and residues treatment aiming at the increase of energy efficiency. Feeding the lignin to an IGCC process, the electric efficiency is increased by 4.4% compared with combustion, which leads to an overall energy efficiency of 53.8%. A detailed sensitivity analysis on energy efficiency is also carried out.     

Process intensification and energy saving of reactive distillation for production of ester compounds

Reactive distillation(RD) process is an innovative hybrid process combining reaction with distillation, which has recently come into sharp focus as a successful case of process intensification. Considered as the most representative case of process intensification, it has been applied for many productions, especially for production of ester compounds. However, such problems existing in the RD system for ester productions are still hard to solve,as the removal of the water which comes from the esterification, and the separation of the azeotropes of ester–alcohol(–water). Many methods have been studying on the process to solve the problems resulting in further intensification and energy saving. In this paper, azeotropic–reactive distillation or entrainer enhanced reactive distillation(ERD) process, reactive extractive distillation(RED) process, the method of co-production in RD process, pressure-swing reactive distillation(PSRD) process, reactive distillation–pervaporation coupled process(RD–PV), are introduced to solve the problems above, so the product(s) can be separated efficiently and the chemical equilibrium can be shifted. Dividing-wall column(DWC) structure and novel methods of loading catalyst are also introduced as the measures to intensify the process and save energy.     

Direct Heat Integration of Independent Processes

The properties of matched streams, the simultaneous operation time, and the distance between integrated processes, are the main factors which determine whether the direct integration is feasible or not. According to whether such synthetic integration is economically better than the separate integration of each process, a mathematical formulation is established. The retrofit of reforming and arene processes in a certain petrochemical factory, which are independent each other, is chosen as a case study. By only considering the simultaneous operation time, two retrofit designs are proposed: one is that each of the two processes is separately integrated by itself, and the other is that the two processes are integrated comprehensively. Under different simultaneous operation hours, the energy-saving effects and the economic profits of the two designs are calculated, and furthermore, the critical simultaneous operation time for direct heat integration of the two processes is obtained. When the actual simultaneous operation time of the two processes is longer than the critical value, the direct heat integration of the two processes is better economically, and otherwise the separate heat integration for each process should be considered.     

考虑环境影响最小化的反应过程的开发

A methodology is presented to identify environmental impact minimization alternative for reaction processes and assess their environmental performance.The potential environmental impact (PEI) scheme can be used to visibly display the transformation relationships among different types of PEI,identify the sources of environmental impacts,and propose alternatives for eliminating of minimizing the impacts.To evaluate the environmental performance of the alternatives effectively,some new indices,such as PEI input rate of non-products,PEI output rate of non-products per profit and the PEI conversion efficiency are proposed.Finally,the application of the methodology is illustrated using an industrial case study.     

间歇化工过程和模型优化调度

Chemical batch processes have become significant in chemical manufacturing.In these processes,large numbers of chemical products are produced to satisfy human demands in daily life.Recently,economy globalization has resulted in growing worldwide competitions in traditional chemical process industry.In order to keep competitive in the global marketplace,each company must optimize its production management and set up a reactive system for market fluctuation.Scheduling is the core of production management in chemical processes.The goal of this paper is to review the recent developments in this challenging area.Classifications of batch scheduling problems and optimization methods are introduced.A comparison of six typical models is shown in a general benchmark example from the literature.Finally,challenges and applications in future research are discussed.     

Simulation of hydrocarbons pyrolysis in a fast-mixing reactor

Currently, thermal decomposition of hydrocarbons for the production of basic petrochemicals (ethylene, propyl-ene) is carried out in steam-cracking processes. Aside from the conventional method, under consideration are alternative ways purposed for process intensification. In the context of these activities, the method of high-temperature pyrolysis of hydrocarbons in a heat-carrier flow is studied, which differs from previous ones and is based on the ability of an ultra-short time of feedstock/heat-carrier mixing. This enables to study the pyrolysis process at high temperature (up to 1500 K) at the reactor inlet. A set of model experiments is conducted on the lab scale facility. Liquefied petroleum gas (LPG) and naphtha are used as a feedstock. The detailed data are obtain-ed on temperature and product distributions within a wide range of the residence time. A theoretical model based on the detailed kinetics of the process is developed, too. The effect of governing parameters on the pyrolysis process is analyzed by the results of the simulation and experiments. In particular, the optimal temperature is detected which corresponds to the maximum ethylene yield. Product yields in our experiments are compared with the similar ones in the conventional pyrolysis method. In both cases (LPG and naphtha), ethylene selectivity in the fast-mixing reactor is substantial y higher than in current technology.     

天然气分散制氢的技术经济分析(英文)

It is well established that hydrogen has the potential to make a significant contribution to the world energy production.In U.S.,majority of hydrogen production plants implement steam methane reforming(SMR) for centralized hydrogen production.However,there is a wide lack of agreement on the nascent stage of using hydrogen as fuel in vehicles industry because of the difficulty in delivery and storage.By performing technological and economic analysis,this work aims to establish the most feasible hydrogen production pathway for automotives in near future.From the evaluation,processes such as thermal cracking of ammonia and centralized hydrogen production followed by bulk delivery are eliminated while on-site steam reforming of methanol and natural gas are the most technologically feasible options.These two processes are further evaluated by comprehensive economic analysis.The results showed that the steam reforming(SR) of natural gas has a shorter payback time and a higher return on investment(ROI) and internal rate of return(IRR).Sensitivity analysis has also been constructed to evaluate the impact of variables like NG feedstock price,capital of investment and operating capacity factor on the overall production cost of hydrogen.Based on this study,natural gas is prompted to be the most economically and technologically available raw material for short-term hydrogen production before the transition to renewable energy source such as solar energy,biomass and wind power.     

间歇过程的故障分析和互锁控制器综合的集成

Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common models used for various decision-making processes is an effective approach. From this point of view, a batch system common model as described by a Petri net is proposed. In this article, a fault diagnosis technique for batch processes is presented using information about fault propagation and the possibilities of integration of fault analysis and controller synthesis are discussed on the basis of the Petri net based common models.     

一种新的基于误差矢量化的选择性神经网络集成方法及其在高密度聚乙烯串级反应过程中的应用(英文)

Chemical processes are complex, for which traditional neural network models usually can not lead to satisfactory accuracy. Selective neural network ensemble is an effective way to enhance the generalization accuracy of networks, but there are some problems, e.g., lacking of unified definition of diversity among component neural networks and difficult to improve the accuracy by selecting if the diversities of available networks are small. In this study, the output errors of networks are vectorized, the diversity of networks is defined based on the error vectors, and the size of ensemble is analyzed. Then an error vectorization based selective neural network ensemble (EVSNE) is proposed, in which the error vector of each network can offset that of the other networks by training the component networks orderly. Thus the component networks have large diversity. Experiments and comparisons over standard data sets and actual chemical process data set for production of high-density polyethylene demonstrate that EVSNE performs better in generalization ability.     

Cultivation of microalgae for biodiesel production: A review on upstream and downstream processing

Fluctuating market price of fossil fuel and overwhelming emission of greenhouse gases to the atmosphere have resulted in climate change and have been a global concern in this decade.Hence,biodiesel has become an alternative option to fossil diesel as it is renewable and environmentally friendly.Nevertheless,this alternative fuel that is usually derived from terrestrial oil crops will cause shortage in food supply and deforestation if mass production is realized.In recent years,cultivation of aquatic microorganism (particularly microalgae) to produce biodiesel is considered as a practical solution due to their high growth rate and ability to synthesize large quantity of lipid within their cell.However,the development of energy and cost-efficiency of microalgae cultivation system are the main issues in producing renewable microalgae biodiesel.Of late,wastewater or organic compost has been used as the cultivation medium as it can provide sufficient nutrients to sustain microalgae growth.Microalgae cultivation method and system are vitally important as these factors undoubtedly affect the final microalgae biomass and lipid yield.In this review,the cultivation system of microalgae,nutrients demanded for microalgae production,cell harvesting and drying,microalgae oil extraction,and utilization of microalgae biomass for biodiesel production are introduced and discussed.It is anticipated to convey clearer perspectives in upstream and downstream processes in microalgae-derived biodiesel production.     

间歇生产过程鲁棒统计监控及其应用

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework, which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.     

A Robust Statistical Batch Process Monitoring Framework and Its Application

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework, which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.     

Decision support for the development,simulation and optimization of dynamic process models

Simulation is besides experimentation the major method for designing,analyzing and optimizing chemical processes.The ability of simulations to reflect real process behavior strongly depends on model quality.Validation and adaption of process models are usually based on available plant data.Using such a model in various simulation and optimization studies can support the process designer in his task.Beneath steady state models there is also a growing demand for dynamic models either to adapt faster to changing conditions or to reflect batch operation.In this contribution challenges of extending an existing decision support framework for steady state models to dynamic models will be discussed and the resulting opportunities will be demonstrated for distillation and reactor examples.     

间歇结晶过程的分批优化

It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control, profile calculated with developed process models with respect to such process parameters may not give an optimal performance when implemented to real processes. This study proposes a batch-to-batch optimization strategy for the estimation of uncertain kinetic.par.ameters in a batch crystallization process of potassium sulfate production. The knowledge of a crystal size distribution of the product at the end of batch operation is used in the proposed methodology. The updated kinetic parameters are applied for determining an optimal operating temperature policy for the next batch run.