合成气制二甲醚三相淤浆床反应器的数学模型研究

A mathematical model for a bubble column slurry reactor is presented for dimethyl ether synthesis from syngas. Methanol synthesis from carbon monoxide and carbon dioxide by hydrogenation and the methanol dehydration are considered as independent reactions, in which methanol, dimethyl ether and carbon dioxide are the key components. In this model, the gas phase is considered to be in plug flow and the liquid phase to be in partly back mixing with axial distribution of solid catalyst. The simulation results show that the axial dispersion of solid catalysts, the operational height of the slurry phase in the bubble column slurry reactor, and the reaction results are influenced by the reaction temperature and pressure, which are the basic data for the scale-up of reactor.     

Domestic Industry News

High-quality, High Purity and High Chrome Refrac-tories Water-coal slurry pressure gasifying technology is apatent technology introduced from Texaco in which coal isused to produce useful organic substances. In the technol-ogy, gasifying furnace is key device. However, high-chrome refractories is key material for the smooth opera-tion of the water-coal slurry pressure gasifier. There areonly three companies in the world, which posses the tech-     

基于ARX-PLS解耦框架下的多回路约束迭代模型预测控制方法(英文)

A multi-loop constrained model predictive control scheme based on autoregressive exogenous-partial least squares （ARX-PLS） framework is proposed to tackle the high dimension, coupled and constraints problems in industry processes due to safety limitation, environmental regulations, consumer specifications and physical restric-tion. ARX-PLS decoupling character enables to turn the multivariable model predictive control （MPC） controller design in original space into the multi-loop single input single output （SISO） MPC controllers design in latent space. An idea of iterative method is applied to decouple the constraints latent variables in PLS framework and recursive least square is introduced to identify ARX-PLS model. This algorithm is applied to a non-square simulation system and a stirred reactor for ethylene polymerizations comparing with adaptive internal model control （IMC） method based on ARX-PLS framework. Its application has shown that this method outperforms adaptive IMC method based on ARX-PLS framework to some extent.     

离线辨识和在线辨识相结合的广义预测控制算法在固定床反应器温度控制中的应用

An improved generalized predictive control algorithm is presented in this paper by incorporating offline identification into onlie identification.Unlike the existing generalized predictive control algorithms.the proposed approach divides parameters of a predictive model into the time invariant and time-varying ones,which are treated respectively by offline and onlie identification algorithms.Therefore,both the reliability and accuracy of the predictive model are improved,Two simulation examples of control of a fixed bed reactor show that this new algorithm is not only reliable and stable in the case of uncertainties and abnormal distrubances,but also adaptable to slow time varying processes.     

多目标进化算法求解过程综合中的混合整数线性规划(MILP)与混合整数非线性规划问题(MINLP)

Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of crame is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.     

基于免疫系统的自适应差分进化算法及在水银氧化动力学参数估计中的应用

A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters’ self-adaptation. The performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm and other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury (Hg) oxidation in flue gas, and satisfactory results are obtained.     

基于混合微分进化算法的生化过程动态参数估计(英文)

Determination of the optimal model parameters for biochemical systems is a time consuming iterative process. In this study, a novel hybrid differential evolution (DE) algorithm based on the differential evolution technique and a local search strategy is developed for solving kinetic parameter estimation problems. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. Some well-known benchmark estimation problems are utilized to test the efficiency and the robustness of the proposed algorithm compared to other methods in literature. The comparison indicates that the present hybrid algorithm outperforms other estimation techniques in terms of the global searching ability and the convergence speed. Additionally, the estimation of kinetic model parameters for a feed batch fermentor is carried out to test the applicability of the proposed algorithm. The result suggests that the method can be used to estimate suitable values of model parameters for a complex mathematical model.     

A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching☆

To address large scale industrial processes, a novel Lagrangian scheme is proposed to decompose a refinery scheduling problem with operational transitions in mode switching into a production subproblem and a blending and delivery subproblem. To accelerate the convergence of Lagrange multipliers, some auxiliary constraints are added in the blending and delivery subproblem. A speed-up scheme is presented to increase the efficiency for solving the production subproblem. An initialization scheme of Lagrange multipliers and a heuristic algorithm to find feasible solutions are designed. Computational results on three cases with different lengths of time hori-zons and different numbers of orders show that the proposed Lagrangian scheme is effective and efficient.     

一种新的生产计划与催化裂化装置过程操作集成的闭环策略

Production planning models generated by common modeling systems do not involve constraints for process operations, and a solution optimized by these models is called a quasi-optimal plan. The quasi-optimal plan cannot be executed in practice some time for no corresponding operating conditions. In order to determine a practi- cally feasible optimal plan and corresponding operating conditions of fluidized catalytic cracking unit （FCCU）, a novel close-loop integrated strategy, including determination of a quasi-optimal plan, search of operating conditions of FCCU and revision of the production planning model, was proposed in this article. In the strategy, a generalized genetic algorithm （GA） coupled with a sequential process simulator of FCCU was applied to search operating conditions implementing the quasi-optimal plan of FCCU and output the optimal individual in the GA search as a final genetic individual. When no corresponding operating conditions were found, the final genetic individual based correction （FGIC） method was presented to revise the production planning model, and then a new quasi-optimal production plan was determined. The above steps were repeated until a practically feasible optimal plan and corresponding operating conditions of FCCU were obtained. The close-loop integrated strategy was validated by two cases, and it was indicated that the strategy was efficient in determining a practically executed optimal plan and corresponding operating conditions of FCCU.     

几种气流床气化炉部分气化指标的对比分析

分析了三种气流床气化炉的氧耗问题、产气量问题和气体成分问题。     

大型煤制合成气技术进展

煤气化技术是洁净煤技术的重要组成部分,各种煤气化炉型和气化技术都有各自的优点和不足之处,选择适合的煤气化技术对煤化工项目至关重要。介绍了目前国内大型煤制合成气中广泛应用的Shell煤气化工艺、Texaco水煤浆气化工艺及近年来研发成功的具有自主知识产权的多元料浆加压气化技术、多喷嘴对置式水煤浆气化技术、两段式干煤粉加压气化技术和四喷嘴对置式干粉煤加压气化技术的工艺特点、应用情况。这些技术将是目前和未来大型煤制合成气的技术支撑。     

Texaco水煤浆气化炉炉膛温度监测手段分析

介绍了Texaco水煤浆气化工艺气化炉炉膛温度控制的重要性,提出了通过利用热电偶直接测量法、甲烷含量与温度的近似线形关系、工艺气组分走势判断法及炉渣与气化炉压差法等,来综合判断气化炉炉温,以备指导实际生产。     

淮化Texaco气化炉备选煤种所用水煤浆分散剂的遴选

研究了多种水煤浆分散剂对安徽淮化Texaco气化炉备选煤种成浆性能的影响。结果表明,萘系分散剂对煤种成浆浓度高、流动性好;木质素类分散剂对煤的成浆浓度较低,流动性较差。相较于分散剂而言,煤质是影响水煤浆成浆性能的最关键的因素。北宿煤的制浆浓度大部分都在65.0%以上,是制备气化用浆性能较好的煤种。满足实际生产能力的要求下,HH分散剂对华亭煤最高制浆浓度达60.5%,ZH分散剂对北宿煤最高制浆浓度达67.0%,对于不同的煤种,不可盲目追求性价比较高、广谱性强的分散剂。     

多喷嘴对置式水煤浆气化技术应用总结

介绍了多喷嘴对置式水煤浆加压气化装置的运行情况,并与德士古气化炉的运行进行了对比.针对多喷嘴对置式水煤浆加压气化装置在运行过程中出现的不足之处,采取了相应的改进措施.     

国内几种气化灰水(黑水)系统的运行评价

主要对国内德士古水煤浆气化装置中几种灰水(黑水)系统的流程加以比较,分别评价了它们各自的特点和缺点,并做出简要的总结.     

德士古煤气化合成气带水问题的分析与探讨

分析了德士古气化炉合成气带水的原因及其对稳定生产的影响，并提出了通过降低热流强度、扩大上升管直径、加大激冷室液面上部分离空间及在气化炉合成气出口管线上设置气水分离器的改进措施。     

水煤浆管道输送压力降的计算方法探讨

根据上海焦化有限公司德士古煤气化装置的实测运行数据得到表述摩擦因子的关联式,用该关联式计算取得的数据与实测值的偏差范围较用Turian方程低。该关联式可以作为工业规模水煤浆输送时计算压力降的依据。同时对该装置水煤浆管道输送的临界流速及维持水煤浆均相流动的最低流速进行了核算,为今后工程设计及生产操作管理提供了依据。     

水煤浆水冷壁气化炉项目总结

日处理煤750 t水煤浆水冷壁气化炉工艺示范装置具有氧气分级供给、气化炉采用水冷壁代替耐火砖、水煤浆进料流程短、喷嘴使用寿命长等特点。在气化压力4.0 MPa条件下,制得的煤气中有效气体(CO+H2)体积分数≥79.7%,碳转化率达98.0%,喷嘴使用寿命超过6个月,基本达到三废零排放。与德士古气化炉相比,采用该技术设备可全部国产化,降低建设投资,经济和环境效益显著。     

水煤浆气化炉安全系统的设计

介绍了德士古水煤浆加压气化炉的安全系统,详细阐述如何进行检测仪表和控制元件的设计来提高安全系统的可靠性,从而有效地实现气化炉系统的安全开车、停车等操作.对大化肥气化装置安全系统的作用、硬件组成、信号的处理和安全联锁也进行了介绍.