Simultaneous integration of water and energy in heat‐integrated water allocation networks

This article proposes a new methodology for simultaneous integration of water and energy in heat‐integrated water allocation networks (WAHEN). A novel disjunctive model is first developed to determine an optimal water allocation network (WAN) where water and energy are integrated in one step. Based on the optimal WAN, a detailed heat exchanger network (HEN) to satisfy the utility target is then synthesized. Although the final network structure is obtained through two steps, the targets of freshwater and utility are optimized simultaneously. The proposed method has specific advantages. First of all, it can capture a tradeoff among freshwater usage, utility consumption, and direct heat transfer by nonisothermal mixing. Second, it can greatly reduce the complexity of subsequent HEN design. Finally, it is effective for simultaneous water and energy integration in large‐scale WAHEN systems. The advantages and applicability of this new method are illustrated by three examples from literature. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2202–2214, 2015     

Simultaneous optimal integration of water utilization and heat exchange networks using holistic mathematical programming

A systematic holistic mathematical programming (HMP) is proposed to formulate a mixed integer nonlinear programming (MINLP) model for one-step optimization of water-allocation and heat exchange network (WAHEN) designs with single- or multi-contaminant water streams. The proposed model formulation and solution strategy are believed to be superior to the available ones in the following aspects. First, a comprehensive representation combining two separate superstructures is adopted to capture the structural characteristics of the integrated WAHEN. Then, a hybrid optimization strategy integrating stochastic and deterministic components is developed for the resulting MINLP model and, also, an interactive iteration method is adopted based on sensitivity analysis to guide the search toward a potential global optimum. Finally, evolutionary strategies and manipulations are executed to enhance WAHEN configurations. Two illustrative examples are presented to demonstrate the validity and advantages of the proposed approach.     

水网络与虚拟水的过程系统工程研究进展

水危机的迫切性已经引起了全世界过程系统工程领域的普遍关注。首先概述了全球和中国水危机的严重情况, 介绍了政府和学术界的对策, 系统地检索了1994年以来对水网络和虚拟水问题发表的文献著作。分3个层次对国内外的研究做了系统综述:①单个企业内水网络系统集成优化, 包括用水网络(WUN)、废水处理网络(WWTN)、总水网络(TWN)和全水网络(CWN)及冷却循环水系统问题、有中水道水网络和间歇水网络问题3个特殊问题;热量和水耗同时最小化的水配置和换热网络问题(WAHEN);多种工艺与能、水网络系统同时集成优化研究;②跨企业多个水网络系统集成优化;③跨地区/国家的虚拟水与产品水足迹研究。这些研究对企业的、跨企业的生态工业园区以及区域产业系统的节水减排和提高水、能的利用效率可以发挥重要作用, 并对解决缺水地区/国家的政策制定提供依据。     

Novel graphical tool for the design of the heat integrated water allocation networks

A new graphical tool has been developed for the HEN design of WAHEN. An ΔH‐F diagram is proposed to deal with the heat exchange matches. Nonisothermal stream mixing and splitting can be achieved by the transformation of stream composite curve in the ΔH‐F diagram. A matching composite curve is proposed for the design of HEN with parallel structure. The structure of HEN can be simplified by adjusting the shape of the matching composite curve. Both small scale and large scale examples are illustrated. Results show that the proposed method is as good as the previous methods for small scale problem, while it gets a better result for large scale problem. © 2015 American Institute of Chemical Engineers AIChE J, 62: 670–686, 2016     

Process‐based graphical approach for simultaneous targeting and design of water network

A new process‐based graphical approach (PGA) is presented for the simultaneous targeting and design of water network. The PGA is extended from the limiting water profile which was developed for flow rate targeting for a water network. Via PGA procedure, apart from locating the minimum freshwater and wastewater flow rate targets, the water network that corresponds to the minimum flow rate targets is also synthesized simultaneously. The proposed approach handles both fixed load (including operations with water loss and/or gain) and fixed flow rate problems equally well. In addition, the approach can be used to synthesize direct reuse/recycle, regeneration reuse/recycling, and total water network. Furthermore, the proposed approach is applicable for water network with multiple freshwater sources. Three literature examples are presented to illustrate the proposed approach. © 2011 American Institute of Chemical Engineers AIChE J, 2011     

基于FDCS技术的城市智能热网控制系统应用设计与功能研究

针对热网控制系统的具体特点和智能热网的功能需求,提出一种基于FDCS技术的城市智能热网控制系统设计方案。介绍了对现场总线设备网络的设计、集控中心功能的设计和数据传输网络的设计方案,并对智能热网控制系统具体实现的高级功能进行探讨性研究,以期推动热网控制领域的技术变革。     

有最大入口浓度限制的单杂质废水处理网络设计

分布式废水处理系统集成的本质特征之一是通过最大程度减少不必要的水流混合量而降低系统的总处理量。根据这一思想,提出了一种基于启发式规则的方法设计废水处理单元有最大入口浓度限制的单杂质废水处理系统。首先依据提出的规则确定处理单元的执行顺序,并在此基础上建立初始网络结构;然后通过计算确定最终网络结构。在设计过程中,上述规则的运用和最终网络结构的确定需要与杂质负荷平衡、夹点确定等废水处理网络设计的基本概念以及入口浓度限制条件相结合。对文献实例的研究表明,结果与数学规划法的求解结果相当,但设计过程更为简单且具有明确的工程意义。     

Distributed model predictive control-oriented network decomposition based on full dynamic response

This article addresses network decomposition for distributed model predictive control (DMPC), which includes two improvements. First, in the weighted input–output bipartite graph construction of a process network, a new measure called frequency affinity is proposed to characterize the input–output interaction considering the full dynamic response and structural information of a process. Then, in community detection, which is used to decompose the process network, the gap metric is added to quantify stability and the loss of control performance of each subsystem. Through the proposed decomposition, the obtained subsystems can be dynamically well-decoupled since both transient and steady-state responses are measured by the frequency affinity. As structural information is considered, the decomposition is consistent with the process physical topology. Furthermore, the utilization of gap metric can facilitate controller design for DMPC. Case studies on a reactor separator process and an air separation process demonstrate the effectiveness of the proposed decomposition method.     

考虑冗余控制的多周期换热网络设计

实际多周期换热网络的设计不但要满足多个离散周期的操作条件要求,还应该满足单个周期下的柔性要求,以补偿实际操作中单周期下可能出现的参数波动。而根据工程经验增加换热面积裕量和采用文献中的最大面积思想进行设计,都会造成多周期换热网络中换热面积的过度冗余,导致资源的浪费和投资成本的增加。针对以上问题,在综合考虑多周期操作条件要求和单周期柔性要求的基础上,提出了一种控制面积冗余的多周期换热网络设计方法。该方法首先在单周期换热网络集成的基础上获取一个初始的多周期换热网络设计方案。然后以此方案为基础,构建一个基于单周期换热网络模型和柔性分析模型的换热网络修正模型,并通过求解该模型获得初始多周期换热网络在各周期下的最优修正方案。通过综合初始多周期换热网络设计和修正方案,即可完成最终的多周期换热网络设计。最后,通过将所得多周期换热网络与文献中所得结果进行对比,验证了方法的有效性。     

A heuristic design method for batch water-using networks of multiple contaminants with regeneration unit

This work develops a heuristic method for the design of batch water-using networks of multiple contaminants with regeneration unit based on the concepts of concentration potential. A water-using network involving regeneration unit can be formed by adding the regenerated stream(s) into the network involving reuse only. In the design procedure of the network operated in a single batch mode, time is taken as the primary factor and concentration potentials as the secondary one. For the networks operated in a repeated mode, the design procedure is similar to that for continuous processes, besides designing the storage tanks with the rules proposed. Continuous regeneration unit is selected in this work. With the proposed method, the network structure corresponding to the minimum freshwater consumption can be obtained. It is shown that the method proposed in this article is simple, effective and has clear engineering meaning.     

Sensitivity and Optimization of Peel Strength Based on Composition of Adhesives for Footwear Industry

In order to contribute to the research and development of adhesives for the footwear industry, this paper aims to develop a model capable to predict and optimize the peel strength from the composition of adhesives. The proposed approach is based on three stages: experimental planning of measurements, global sensitivity analysis for uncertainty propagation, and optimization procedure. The design variables are the weight percentages of the solid raw material constituents such as polyurethane, resins, and additives of the adhesive joint. Considering the experimental results obtained for Taguchi design points as input/output patterns, an artificial neural network (ANN) is developed based on supervised evolutionary learning. Using the developed ANN a global sensitivity analysis procedure is implemented and the variability of the structural response of adhesive joint is studied. The optimal solution for adhesives composition for maximum peel strength is investigated based on ANN model and using a genetic algorithm. The proposed approach is able to predict the optimal peel strength including its sensitivity to uncertainties. The results show that the sensitivities of design variables belonging to polyurethane and additive groups are important for optimal adhesive joint. The optimal peel strength based on proposed approach is consistent with the experimental testing data.     

Prototype Tool for Inherent Safety Level Assessment of a Heat Exchanger Network

The inherent safety level (ISL) assessment of a heat exchanger network plays a vital role in developing its inherently safer design. New essential safety indices, i.e., inherent safety index for shell and tube heat exchanger (ISISTHE) and overall safety index for heat exchanger network (OSIHEN), are introduced to overcome this potential gap. A prototype tool is proposed by integrating these indices to a process design simulator via object linking and embedded automation. The heat exchanger network of an ammonia synthesis process and a steam reforming unit are presented as a case study. In conclusion, this prototype tool was found to have the potential to figure out a dangerous heat exchanger in a network.     

NEURAL NETWORK-BASED PREDICTIVE CONTROL FOR MULTIVARIABLE PROCESSES

In this paper, the systematic derivations of setting up a nonlinear model predictive control based on the neural network are presented. This extends our previous work (Chen, 1998) into a multivariable system to explore the characteristics of the design. There are two stages for the development of nonlinear neural network predictive control: a neural network model and a control design. In the neural network model design, a parallel multiple-input, single-output neural network autoregressive with a model of exogenous inputs (NNARX) is proposed for multistep ahead predictions. In control design, the controller with extended control horizon is developed. The Levenberg-Marquardt algorithm is applied to training the NNARX model. Also, the sequential quadratic programming is used to search for the optimal manipulated inputs. The gradient of the objective function and constraints that require computation of Jacobian matrices are completely derived for optimization calculation. To demonstrate the control ability of MIMO cases, the proposed method is applied through two nonlinear simulation problems.     

Neural network-based predictive control for multivariable processes

In this paper, the systematic derivations of setting up a nonlinear model predictive control based on the neural network are presented. This extends our previous work (Chen, 1998) into a multivariable system to explore the characteristics of the design. There are two stages for the development of nonlinear neural network predictive control: a neural network model and a control design. In the neural network model design, a parallel multiple-input, single-output neural network autoregressive with a model of exogenous inputs (NNARX) is proposed for multistep ahead predictions. In control design, the controller with extended control horizon is developed. The Levenberg-Marquardt algorithm is applied to training the NNARX model. Also, the sequential quadratic programming is used to search for the optimal manipulated inputs. The gradient of the objective function and constraints that require computation of Jacobian matrices are completely derived for optimization calculation. To demonstrate the control ability of MIMO cases, the proposed method is applied through two nonlinear simulation problems.     

基于经验规则的数学规划法快速设计多杂质用水网络

综合了夹点规则、排序思路等经验,提出了基于经验规则的数学规划法来快速设计多杂质用水网络。由于获取准确的用水过程顺序是剔除一些不必要流股、简化用水网络数学模型的关键,因此,基于对用水过程极限数据的分析和对用水过程的理解,提出了用水过程供水和受水的排序方法,并设定必要的水夹点规则、序列和逼近规则、混合规则以剔除不必要的水网络结构,达到简化模型、降低网络结构维数的目的,最后在LINGO软件上编写程序进行求解。通过三实例分析得知,设定经验规则后能够有效地降低模型规模、减少模型的非线性变量数、缩短模型的求解时间,并能够得到最优的设计方案。     

A robust possibilistic programming approach for pharmaceutical supply chain network design

In this paper, a bi-objective mixed integer linear programming (BOMILP) model is developed for a pharmaceutical supply chain network design (PSCND) problem. The model helps to make several decisions about the strategic issues such as opening of pharmaceutical manufacturing centers and main/local distribution centers along with optimal material flows over a mid-term planning horizon as the tactical decisions. It aims to concurrently minimize the total costs and unfulfilled demands as the first and second objective functions. Since the critical parameters are tainted with great degree of epistemic uncertainty, a robust possibilistic programming approach is used to handle uncertain parameters. In order to verify and analyze the proposed model, it is tested on a real case study and managerial insights are provided.     

Computational strategies for large-scale MILP transshipment models for heat exchanger network synthesis

Determining the minimum number of units is an important step in heat exchanger network synthesis (HENS). The MILP transshipment model (Papoulias and Grossmann, 1983) and transportation model (Cerda and Westerberg, 1983) were developed for this purpose. However, they are computationally expensive when solving for large-scale problems. Several approaches are studied in this paper to enable the fast solution of large-scale MILP transshipment models. Model reformulation techniques are developed for tighter formulations with reduced LP relaxation gaps. Solution strategies are also proposed for improving the efficiency of the branch and bound method. Both approaches aim at finding the exact global optimal solution with reduced solution times. Several approximation approaches are also developed for finding good approximate solutions in relatively short times. Case study results show that the MILP transshipment model can be solved for relatively large-scale problems in reasonable times by applying the approaches proposed in this paper.     

基于IP网络的NCS中通信网络动态模型的建立

对于一个基于IP网络的控制系统 (NCS),该IP网络上的其它数据流严重地影响着NCS的控制性能。为此,提出了一个动态模型来描述NCS数据传输过程中的时延和丢包。基于该模型,通过计算机仿真考察了不同网络干扰流对单输入单输出常规PIDNCS开环、闭环特性的影响。仿真结果表明:对于采用常规PID控制器的NCS,网络负荷对其控制性能影响很大;当网络负荷过大时,该NCS可能变得不稳定。     

Optimization of refinery hydrogen network based on chance constrained programming

Deterministic optimization approaches have been developed and used in the optimization of hydrogen network in refinery. However, uncertainties may have a large impact on the optimization of hydrogen network. Thus the consideration of uncertainties in optimization approaches is necessary for the optimization of hydrogen network. A novel chance constrained programming (CCP) approach for the optimization of hydrogen network in refinery under uncertainties is proposed. The stochastic properties of the uncertainties are explicitly considered in the problem formulation in which some input and state constraints are to be complied with predefined probability levels. The problem is then transformed to an equivalent deterministic mixed-integer nonlinear programming (MINLP) problem so that it can be solved by a MINLP solver. The solution of the optimization problem provides comprehensive information on the economic benefit under different confidence levels by satisfying process constraints. Based on this approach, an optimal and reliable decision can be made, and a suitable compensation between the profit and the probability of constraints violation can be achieved. The approach proposed in this paper makes better use of resources and can provide significant environmental and economic benefits. Finally, a case study from a refinery in China is presented to illustrate the applicability and efficiency of the developed approach.     

基于二维传递模型的反应器网络综合

反应器网络综合的任务在于寻求适宜的反应器类型、尺寸及反应单元间的连接关系并确定各反应器的操作条件,其研究方法主要包括超级结构法和目标法,采用的基本单元均为一维理想模型。文中同时考虑传质、传热、流体流动以及反应动力学,通过偏微分方程描述轴向及径向上的温度、浓度分布,建立了二维反应器模型。基于该二维传递模型,采用状态空间构建反应器网络,并以年度总费用为目标函数评价反应器系统的经济性。最后,以提出的模型对环氧丙烷反应器网络进行了优化设计,实例验证了方法的有效性。