Cooperative optimal power flow with flexible chemical process loads

Power systems operations involve dispatching generation capacity and ancillary services as required to sustain reliable functioning of the electric grid. The dispatch schedules are determined by solving power flow calculations that incorporate models of the network components in real time as the power grid conditions change. Electricity intensive chemical processes can potentially provide grid support services and a closer coordination between process and grid operations can be beneficial. This cooperation is hindered by the lack of suitable process models, which appropriately protect process information. We propose a means to model the grid-relevant dynamics of chemical processes, and a framework for embedding such models in optimal power flow calculations. We present an extensive case study concerning cooperative demand-response operation for an electricity-intensive chemical process, chlor-alkali production. The results indicate significant flexibility and economic benefits both at the utility and at the end-user levels.     

Flow field design and optimization of high power density vanadium flow batteries: A novel trapezoid flow battery

Vanadium flow battery (VFB) is one of the preferred techniques for efficient large‐scale energy storage applications. The key issue for its commercialization is cost reduction, which can be achieved by developing high power density VFB stacks. One of the effective strategies for developing high power density stacks is to enhance the mass transport by performing flow field design. Based on the maldistribution characteristics of concentration polarization inside a conventional rectangular flow battery (RFB), a novel trapezoid flow battery (TFB) was first proposed. Furthermore, a practical and general strategy, consisting of a stepping optimization method and an arithmetic progression model, has been developed for the TFB's structure optimization. By combining numerical simulation with charge‐discharge test of the magnified stacks, it was verified that mass transport enhancement and performance improvement of the optimized TFB, with significant increments in voltage efficiency and electrolyte utilization, allowed it to possess great superiority over the RFB. © 2017 American Institute of Chemical Engineers AIChE J, 64: 782–795, 2018     

A modeling strategy for integrated batch process development based on mixed-logic dynamic optimization

This paper introduces an optimization-based approach for the simultaneous solution of batch process synthesis and plant allocation, with decisions like the selection of chemicals, process stages, task-unit assignments, operating modes, and optimal control profiles, among others. The modeling strategy is based on the representation of structural alternatives in a state-equipment network (SEN) and its formulation as a mixed-logic dynamic optimization (MLDO) problem. Particularly, the disjunctive multistage modeling strategy by Oldenburg and Marquardt (2008) is extended to combine and organize single-stage and multistage models for representing the sequence of continuous and batch units in each structural alternative and for synchronizing dynamic profiles in input and output operations with material transference. Two numerical examples illustrate the application of the proposed methodology, showing the enhancement of the adaptability potential of batch plants and the improvement of global process performance thanks to the quantification of interactions between process synthesis and plant allocation decisions.     

改进的信息流图及其在精馏塔建模与仿真中的应用

计算机动态建模与仿真中,人们最常用的用以辅助进行交流和讨论以及文档化相关成果与决策的分析、设计方法及表示法是信息流图（information flow diagram）。在前人研究的基础上,提出了一种改进的、更为完善的信息流图表示法。该表示法共包含三大类、九小类组成元素,基本能够完全覆盖计算机动态建模与仿真中所有种类的数学公式及其他模型表达方式。最后,以精馏塔的动态建模与仿真为例,详细说明了改进的信息流图的具体应用情况。事实证明,改进的信息流图不仅为相关工作人员提供了良好的沟通媒介,还使人们能够更加容易地从先前的仿真模型构建项目中复用需求和设计组件等,从而提高了仿真模型构建的效率和质量。     

Distributional uncertainty analysis and robust optimization in spatially heterogeneous multiscale process systems

Multiscale models have been developed to simulate the behavior of spatially‐heterogeneous porous catalytic flow reactors, i.e., multiscale reactors whose concentrations are spatially‐dependent. While such a model provides an adequate representation of the catalytic reactor, model‐plant mismatch can significantly affect the reactor's performance in control and optimization applications. In this work, power series expansion (PSE) is applied to efficiently propagate parametric uncertainty throughout the spatial domain of a heterogeneous multiscale catalytic reactor model. The PSE‐based uncertainty analysis is used to evaluate and compare the effects of uncertainty in kinetic parameters on the chemical species concentrations throughout the length of the reactor. These analyses reveal that uncertainty in the kinetic parameters and in the catalyst pore radius have a substantial effect on the reactor performance. The application of the uncertainty quantification methodology is illustrated through a robust optimization formulation that aims to maximize productivity in the presence of uncertainty in the parameters. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2374–2390, 2016     

A computationally-cost effective model for fluid flow in redox flow batteries

Redox flow batteries (RFBs) hold great potential for large-scale, extended-duration stationary energy storage. Here, a novel computationally cost-effective hydraulic-electrical analogous model (HEAM) for fluid flow in RFBs is developed. The HEAM demonstrated that lowering the electrode compression and enhancing the channel area lowers the pump power loss independent of the flow fields and electrodes. Additionally, the HEAM helped elucidate the deficiencies of flow distribution in interdigitated flow fields (IFFs) and suggested designing wider manifolds and/or shorter channels improve the flow distribution. Moreover, the HEAM suggested shallower and/or wider channels, and more permeable electrodes enhance the flow penetration rate above the channels. Finally, the HEAM showed that the average penetration depth in the electrode above the ribs (h_pen) was the critical parameter in the fluid-flow modeling of IFFs and was inversely proportional to the permeability. Hence, there is a trade-off between the pump power loss and h_pen when configuring electrode permeability.     

化工过程设计的多目标不确定优化研究

In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and environmental impact is minimized simultaneously. Moreover, the random behavior in the process,property, market fluctuation, errors in model prediction and so on would affect the performance of a process. Therefore, it is essential to develop a MOO methodology under uncertainty. In this article, the authors propose a generic and systematic optimization methodology for chemical process design under uncertainty. It aims at identifying the optimal design from a number of candidates. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.     

一种提高微生物发酵单位的新优化控制策略

为了提高微生物发酵单位,提出了支持向量机（SVM）与基于实数编码遗传算法（RGA）相互耦联的优化控制策略。为解决发酵参数之间的耦合问题,进一步引入了模式的概念。SVM建立微生物发酵过程的预估模型,RGA以此模型为适应度函数计算最优控制模式。此策略应用于青霉素发酵过程的优化控制,效价比没有实施优化控制策略的生产结果提高了22.88％。     

A generalized reduced fluid dynamic model for flow fields and electrodes in redox flow batteries

High-dimensional models typically require a large computational overhead for multiphysics applications, which hamper their use for broad-sweeping domain interrogation. Herein, we develop a modeling framework to capture the through-plane fluid dynamic response of electrodes and flow fields in a redox flow cell, generating a computationally inexpensive two-dimensional (2D) model. We leverage a depth-averaging approach that also accounts for variations in out-of-plane fluid motion and departures from Darcy's law that arise from averaging across three-dimensions (3D). Our resulting depth-averaged 2D model successfully predicts the fluid dynamic response of arbitrary in-plane flow field geometries, with discrepancies of <5% for both maximum velocity and pressure drop. This corresponds to reduced computational expense, as compared to 3D representations (<1% of duration and 10% of RAM usage), providing a platform to screen and optimize a diverse set of cell geometries.     

Study on optimization of actinide oxalate precipitation process in a vortex flow reactor

Oxalate precipitation process is globally accepted and is the current choice for conversion of actinide nitrates to their oxides. A vortex flow reactor with magnetic stirrer is found to be a better option for a hassle-free operation of batch as well continuous actinide reconversion process. Utilization of magnetic stirrer as an alternate for the conventional mechanical stirrer eliminates corrosion-related issues as none of the metal parts are in contact with nitric acid as well as oxalic acid solution. Moreover, this alternative system ensures a maintenance-free process. Optimization of various process conditions in a vortex reactor was accomplished using cerium nitrate as a surrogate for actinide nitrate and the results obtained were compared with that of pitched blade mechanical stirrer. About 40 L of thorium nitrate solution was successfully precipitated by the optimized procedure in a vortex reactor.     

一种基于测量的双层动态优化策略及其在青霉素发酵过程中的应用(英文)

One measurement-based dynamic optimization scheme can achieve optimality under uncertainties by tracking the necessary condition of optimality (NCO-tracking), with a basic assumption that the solution model remains invariant in the presence of al kinds of uncertainties. This assumption is not satisfied in some cases and the stan-dard NCO-tracking scheme is infeasible. In this paper, a novel two-level NCO-tracking scheme is proposed to deal with this problem. A heuristic criterion is given for triggering outer level compensation procedure to update the solution model once any change is detected via online measurement and estimation. The standard NCO-tracking process is carried out at the inner level based on the updated solution model. The proposed approach is il ustrated via a bioreactor in penicil in fermentation process.     

A two-level measurement-based dynamic optimization strategy for a bioreactor in penicillin fermentation process

One measurement-based dynamic optimization scheme can achieve optimality under uncertainties by tracking the necessary condition of optimality (NCO-tracking), with a basic assumption that the solution ...     

动力电池双向热管理系统性能分析与优化

基于工质相变热虹吸效应,提出了动力电池双向热管理系统,通过改变工质充注量,60~220 g时,试验测试了该系统的双向热管理性能,并据此进行系统优化。结果表明：该热管理系统的正常运行有一个最低充注量。系统优化前,加热工况,系统换热功率受充注量的影响小;散热工况,系统的换热功率随充注量的增加而增大,随电池箱初始温度升高而增大,且强制散热效果要优于自然散热;相同充注量,换热板表面的最大温差随电池箱初始温度升高而增大,在3C放电倍率,无法控制电池表面温度低于45℃。系统优化后,圆管换热板系统的换热效果要优于矩形管换热板系统,且在3C放电倍率能将电池表面温度降低至43.4℃,换热板的温度一致性更好。     

Investigating the use of path flow indicators as optimization drivers in batch process retrofitting

Improvement of batch processes has gained much attention in industry due to the competitive market and stricter environmental legislation. This paper focuses on a process flowsheet decomposition based methodology resulting in path flow indicators which are able to highlight process alternatives with an improved performance. The novel aspects introduced in this methodology are the implementation of a new path flow indicator category that focuses on unit occupancy time and the multi-objective process assessment in order to reveal sustainable retrofitting actions. Furthermore, the retrofit alternatives are not only classified according to the diverse objective functions but also to the differences observed in the path flow indicator matrix of the generated retrofit alternatives compared to the base case. This classification enables a more detailed analysis of the retrofit alternative impact and illustrates the potential of path flow indicators as optimization drivers. The methodology is exemplified in an industrial batch process case study.     

乙烯深冷分离中变温冷却过程制冷系统的设计与优化

根据乙烯装置中的用冷需求,将乙烯装置的深冷分离过程分为变温冷却过程和定温冷凝过程,变温冷却过程指的是裂解气的预冷过程,定温冷凝过程指的是乙烯装置中各塔塔顶冷凝器中的换热;分析了乙烯-丙烯复叠制冷系统的换热集成曲线,可知在裂解气的预冷阶段,冷热物流换热温差大。提出一种组合制冷系统,它集成了纯工质复叠制冷和混合冷剂制冷,其中的多元混合冷剂制冷系统为乙烯深冷分离的变温换热过程提供冷量。并用Aspen Plus软件对混合冷剂系统进行建模,使用遗传算法优化,优化结果表明在替代原制冷系统6895.5 kW冷量负荷的情况下,功耗降低521.6 kW,节能14.7%。     

工业结晶过程的多相流与粒数衡算的CFD耦合求解

考虑不同尺寸的晶体为不同的分散相,通过有限体积法差分不同尺寸组的晶体求解粒数衡算方程,建立了质量衡算与粒数衡算之间的联系,在考虑晶体成核和生长的条件下,建立了稳态结晶过程的粒数衡算方程与多相流方程的耦合求解方法,得到了工业结晶过程的计算流体力学模拟模型。使用商业软件ANSYS CFD,采用该模型对DTB 型工业结晶器中氯化钾-水体系的结晶过程进行了模拟,最终获得不同尺寸晶体的流场和固体含量的分布信息,从而实现结晶过程的仿真模拟。对部分模拟结果与实验值进行了比较,结果表明模拟结果与实验结果吻合较好。     

Comparison of contact-force models for the simulation of collisions in DEM-based granular flow codes

The distinct element method (DEM) has proven to be reliable and effective in characterizing the behavior of particles in granular flow simulations. However, in the past, the influence of different force-displacement models on the accuracy of the simulated collision process has not been well investigated. In this work, three contact force models are applied to the elementary case of an elastic collision of a sphere with a flat wall. The results are compared, on a macroscopic scale, with the data provided by the experiments of Kharaz et al. (Powder Technol. 120 (2001) 281) and, on a microscopic scale, with the approximated analytical solution derived by Maw et al. (Wear 38 (1976) 101. The force-displacement models considered are: a linear model, based on a Hooke-type relation; a non-linear model, based on the Hertz theory (J. Reine Angew. Math. 92 (1882) 156) for the normal direction and the no-slip solution of the theory developed by Mindlin and Deresiewicz (Trans. ASME. Ser. E, J. Appl. Mech. 20 (1953) 327) for the tangential direction; a non-linear model with hysteresis, based on the complete theory of Hertz and Mindlin and Deresiewicz for elastic frictional collisions. All the models are presented in fully displacement-driven formulation in order to allow a direct inclusion in DEM-based codes.The results show that, regarding the values of the velocities at the end of collision, no significant improvements can be attained using complex models. Instead, the linear model gives even better results than the no-slip model and often it is equivalent to the complete Mindlin and Deresiewicz model. Also in the microscopic scale, the time evolution of the tangential forces, velocities and displacements predicted by the linear model shows better agreement with the theoretical solution than the no-slip solution. However, this only happens if the parameters of the linear model are precisely evaluated.The examination of the evolution of the forces, velocities and displacements during the collision emphasizes the importance of correct accounting for non-linearity in the contact model and micro-slip effects. It also demonstrates how these phenomena need to be considered into the model in order to perform deeper analyses on granular material in motion and, in general, for systems sensitive to the actual force or displacement. For these cases, more accurate models such as the complete Mindlin and Deresiewicz model should be addressed.     

A teaching methodology based on Mathcad for improving the calculation of pumping power

Some of the most important engineering skills required nowadays are related with the management of computational tools. This study proposes the implementation of a novel teaching methodology for improving the calculation of pumping power by using the Mathcad software. This methodology includes: (1) training courses on initiation to Mathcad, (2) the delivery of a report with theoretical considerations about pumping power, the problem statement, the traditional procedure to solve it, as well as the main indications to do it with Mathcad, and (3) a virtual platform conceived as a meeting space. The assessment of this educational experience, which was carried out with the second-year chemical engineering students enrolled in the Fluid Flow course, revealed that Mathcad is a powerful computational tool for them. Thus, it eliminates the mathematical difficulties, facilitates the understanding of the phenomenon under consideration and the study that the input variables exert on the solution, and also increases the motivation of the students for solving other engineering problems. Therefore, these results support the hypothesis that computational tools like Mathcad direct chemical engineering students towards successful learning.