Rather the Rule than the Exception: Non-Convex Pareto Sets and their Navigation in Distillation Processes

Novel algorithms for adaptive approximation and interactive navigation of Pareto sets are applied to various homogeneous distillation processes with recycle streams within an industrial flowsheet simulator. The adaptive approximation scheme shows that the Pareto set consists of both convex and non-convex regions when the product purities are maximised while minimising the total heat duties. It is illustrated how such Pareto sets can be navigated interactively using a ray tracing technique. Our results suggest that the occurrence of non-convex regions in the Pareto sets is due to recycle streams in the flowsheets and is therefore the rule rather than the exception in multi-objective optimisation of flowsheet simulations in chemical engineering.     

Computer aided flowsheet drawing—II: Stream layout and drawing

A methodology for machine layout of process streams involving multiple directional changes given the equipment layout and stream connection information is formulated. Also considered are the drawing of these streams and of various process equipment symbols as well as the layout and drawing of peripheral flowsheet symbols and messages. The key concepts involved are the use of a coded grid representation of the drawing space, a structural classification of stream configurations, efficient constructions for generating stream paths, and the formulation of a ranking of stream paths. A program package implementing the methodology which includes a simple yet flexible data structure for generating and storing equipment symbols is discussed and example flowsheet are given.     

Extension of multiunit global optimisation to three‐input systems

Finding the global optimum of an objective function has been of interest in many disciplines. Recently, a global optimisation technique based on multiunit extremum seeking has been proposed for scalar and two‐input systems. The idea of multiunit extremum‐seeking is to control the gradient evaluated using finite difference between two identical units operating with an offset. For scalar systems, it was shown that the global optimum could be obtained by reducing the offset to zero. For two‐input systems, the univariate global optimisation is performed on the circumference of a circle of reducing radius. In this study, the concept is extended to three‐input systems where the circle of varying radius sits on a shrinking sphere. The key contribution lies in formulating the rotation required to keep the best point found in the search domain. The theoretical concepts are illustrated on the global optimisation of several examples. Comparison results with other competitive methods show that the proposed technique performs well in terms of number of function evaluations and accuracy. © 2011 Canadian Society for Chemical Engineering     

Optimisation of petroleum refinery water network systems retrofit incorporating reuse,regeneration and recycle strategies

Scarcities in freshwater supply and increasingly stringent rules on wastewater discharges have emerged as major environmental concerns for petroleum refineries. Hence, this work attempts to develop an optimisation framework for refinery water network systems design and retrofit that integrates the complementary advantageous features of water pinch analysis (WPA). The framework explicitly incorporates water minimisation strategies by first postulating a superstructure representation that embeds all feasible flowsheet alternatives for implementing water reuse, regeneration and recycle (W3R) opportunities. Subsequently, a nonlinear programming (NLP) model is formulated based on the superstructure and computational experiments on a real‐world case study are conducted using the GAMS/CONOPT3 modelling language platform. Post‐optimality analysis on the numerical results are performed to achieve the desired water reuse quality, hence presenting a viable framework to aid decision‐making in water network systems synthesis. © 2011 Canadian Society for Chemical Engineering     

Modelling and optimisation of continuous catalytic regeneration process using bee colony algorithm

The continuous catalytic regeneration (CCR) reforming process optimisation leads to nonlinear programming with nonlinear quality constraints such as octane number and coke concentration on the catalytic particles. A typical CCR reforming process consists of four reactors with recycle. The reaction patterns and reactors have been mathematically modelled on a base of 12‐lumped kinetics reaction network derived from literature. The bee colony optimisation (BCO) algorithm is one of the most recent and efficient swarm intelligence‐based algorithms which simulates the foraging behaviour of honey bee colonies. The performance of the BCO algorithm in the process optimisation was compared with the genetic algorithm (GA). In the present work, BCO algorithm was used for optimising the CCR reforming process. The results show that the BCO algorithm reaches a better optimum point in a lower evaluation time and higher convergence rate with respect to the GA. © 2012 Canadian Society for Chemical Engineering     

The multi-period optimisation of an amine-based CO2 capture process integrated with a super-critical coal-fired power station for flexible operation

In this work, we present a model of a super-critical coal-fired power plant integrated with an amine-based CO₂ capture process. We use this model to solve a multi-period dynamic optimisation problem aimed at decoupling the operation of the power plant from the efficiency penalty imposed by the CO₂ capture plant, thus providing the power plant sufficient flexibility to exploit price variation within an electricity market. We evaluate four distinct scenarios: load following, solvent storage, exhaust gas by-pass and time-varying solvent regeneration. The objective is to maximise the decarbonised power plant's short run marginal cost profitability. It is found that while the solvent storage option provides a marginal improvement of 4% in comparison to the load following scenario, the exhaust gas bypass scenario results in a profit reduction of 17% whereas the time-varying solvent regeneration option increases the profitability of the power plant by 16% in comparison to the reference scenario.     

Equation‐oriented simulation and optimization of process flowsheets incorporating detailed spiral‐wound multistream heat exchanger models

Multiple chemical processes rely on multistream heat exchangers (MHEXs) for heat integration, particularly at cryogenic temperatures. Owing to their geometric complexity, the detailed design of MHEXs is typically iterative: the exchanger geometric parameters are selected to match process specifications resulting from a flowsheet optimization step; then, the flowsheet is reoptimized with the predictions of the MHEX model, and these steps are repeated until a convergence criterion is met. This paper presents a novel framework that allows—for the first time, to our knowledge—for the simultaneous optimization of the process flowsheet and the detailed MHEX design. Focusing on spiral‐wound MHEXs, we develop an equation‐oriented exchanger model using industry‐accepted heat transfer and pressure drop correlations for single‐phase and multiphase streams. We embed this model in our previously developed pseudo‐transient equation‐oriented process simulation and optimization framework. We demonstrate our approach on an industrial case study, the PRICO^® natural gas liquefaction process. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3778–3789, 2017     

Design of mixed energy‐integrated batch process networks by Pseudo‐direct approach

In this article, a novel framework for the design of mixed (combined direct and indirect) integration for batch process systems is presented. The framework is based on the concept of pseudo‐direct energy integration (PDEI) which reformulates indirect integration as direct integration using pseudo‐process streams. Two algorithms are presented to achieve energy integration for batch processes operating cyclically (in a campaign mode). The first algorithm targets maximization of energy recovery and overcomes the limitations of some of the existing contributions for design of mixed integrated systems. The second algorithm provides a network reduction methodology to generate a cadre of integrated designs while exploring the trade‐off between capital (number of heat exchangers and storage units) and operating costs (utility consumption). The proposed framework is illustrated using a benchmark example of two hot and two cold streams. © 2017 American Institute of Chemical Engineers AIChE J, 63: 55–67, 2018     

Economic Design of Biofilter Systems

This paper offers an easy-to-use design model for the minimum net present cost of a biofilter system, allowing for compaction of the bed. It compares the two-variable graphical optimisation approach with short-cut methods having analytical solutions. © 1997 SCI.     

Integrated design of diesel hydrotreating processes

This work presents an integrated approach for the design of diesel hydrotreating processes employing a simulated annealing optimisation algorithm. The modelling of reactor, separation and heat recovery system for diesel hydrotreating processes is discussed, and a novel optimisation framework is developed for the design of complex refinery processes. A comparison with conventional approach to process design, i.e. sequential evolution of design, is given to illustrate the ability of proposed approach to obtain overall hydrotreating process designs with minimum total annualised costs. The proposed integrated approach takes into account the trade-offs between capital and operating costs, as well as interactions between the hydrotreater, distillation column, and the associated heat exchanger network.     

考虑多对耦合源阱的氢网络优化方法及其应用

在氢网络中,氢源氢阱通常连接于同一个耗氢反应器,为耦合源阱;反应器操作参数的改变影响该耦合源阱参数。在同一个氢网络中可能存在多对耦合源阱,考虑多对耦合源阱的氢网络优化能够进一步为炼厂降低氢耗,提高经济效益。通过分析氢网络的公用工程与多对耦合源阱的关系,推导确定了公用工程迁量与反应器耗氢以及耦合源阱之间的方程。据此建立了耗氢反应器参数和氢网络图像集成优化方法。案例研究表明,该方法简单、容易理解,能够直观给出公用工程迁量与反应器进口温度之间的关系。     

Tuning of NMPC controllers via multi-objective optimisation

Nonlinear Model Predictive Control (NMPC) is a powerful technique that can be used to control many industrial processes. Different and often conflicting control objectives, e.g., reference tracking, disturbance rejection and minimum control effort, are typically present. Most often these objectives are translated into a single weighted sum (WS) objective function. This approach is widespread because it is easy to use and understand. However, selecting an appropriate set of weights for the objective function is often non-trivial and is mainly done by trial and error. The current study proposes a systematic procedure for tuning Nonlinear MPC based on multi-objective optimisation methods. Advanced methods allow an efficient solution of the multi-objective problem providing a systematic overview of the controller behaviour. Moreover, through analytic relations it is possible to link a solution obtained with these novel methods to a set of weights for a weighted sum objective function. Applying this set of weights causes the WS to generate the same solution as obtained with the advanced method. Hence, an appropriate controller can be selected based on the alternatives generated by the advanced method, while the corresponding weights for a WS can be derived for implementing the controller in practice. The procedure is successfully tested on two benchmark applications: the Van de Vusse reactor and the Tennessee Eastman plant.     

考虑温度约束的单杂质水网络优化

实际用水过程有温度的要求,在用水网络集成中考虑温度的约束,使水耗和能耗同时降低,具有重要的意义。此外,过程系统中还存在只有温度限制的与用水无关的过程流股,将水网络中的水流股与其同时考虑热集成,可以使能量得到更合理的分配利用。在全过程系统能量集成的背景下,建立了对应的水网络优化方法。首先使用现有的废水直接回用水网络LP模型求解初始水网络并提取流股数据,然后在4条非等温混合规则的判断下,依次比较水网络流股与背景夹点、全过程夹点的关系,以排除不合理的非等温混合,最后以年总费用最低为目标进行全过程系统的热集成。使用本文提出的方法对某案例进行优化,得到的年总费用减少了6.27%,证明了该方法的可行性。     

A Newton-Raphson based strategy for exploiting latency in dynamic simulation

Latency [6] in dynamic simulation is a consequence of the difference between the dynamic behavior of different units that make up a flowsheet. Taking advantage of latency is essential to reduce the computation time in dynamic simulation. It is observed that in dynamic simulation there is a parallelism between the degree of dynamical activity of a unit and the computational effort required to realize this activity. An algorithm is presented to exploit this parallelism by avoiding some or all the steps involved in solving the corrector equations in the numerical integration process by the Newton-Raphson method. Unlike conventional ones, the proposed algorithm has no approximations built into it and solves the correct model of the flowsheet at each step of the integration. The algorithm is tested on the example problem and it is shown that significant savings in computation time can be achieved.     

Optimal control of batch processes using particle swam optimisation with stacked neural network models

An optimal control strategy for batch processes using particle swam optimisation (PSO) and stacked neural networks is presented in this paper. Stacked neural network models are developed form historical process operation data. Stacked neural networks are used to improve model generalisation capability, as well as provide model prediction confidence bounds. In order to improve the reliability of the calculated optimal control policy, an additional term is introduced in the optimisation objective function to penalize wide model prediction confidence bounds. The optimisation problem is solved using PSO, which can cope with multiple local minima and could generally find the global minimum. Application to a simulated fed-batch process demonstrates that the proposed technique is very effective.     

Analysis of the Relation between Coupled Sink and Purification Based on Hydrogen Network Integration

In a hydrogen network, sinks and sources are generally connected to reactors or purifiers, which affect their compositions and flow rates. The relationship between these streams is studied based on the integration of the hydrogen network to identify the feasible and optimal operating conditions of reactors and purifiers. Equations are deduced to describe the quantitative relationship between hydrogen consumption, hydrogen concentration, flow rates of coupled sink and source, purification feed, and purified product. The purification and hydrogen‐consuming reactor parameters can be optimized in the design and operation stage of a hydrogen network. The case study proves that the proposed method is simple, easy to understand, and can be applied to identify the variation trend line and feasible region accurately without tedious calculation.     

Evolutionary design of optimum distillation column sequence

Synthesis of the optimum distillation column sequence (DCS), which incorporates a huge search space composed of both conventional and complex arrangements, is a highly complicated combinatorial problem in the field of chemical process design and optimisation. In this study, a novel procedure for the synthesis of optimum DCS proposed by Boozarjomehry et al. [Boozarjomehry et al., Can. J. Chem. Eng. 87, 477–492 (2009)] is expanded to include the complex distillation arrangements. The method is based on evolutionary algorithms, and the total annual cost (TAC) is the main criterion used to screen alternatives. Efficient procedure has been proposed for encoding mechanism to include and classify various complex arrangements together with conventional distillation columns. All columns existing in each DCS alternative are designed using the most recommended short‐cut methods to estimate the TAC of the DCS. Four standard benchmark case studies are carried out to clearly demonstrate the excellent performance of the proposed method. The produced results for these problems indicate that the proposed method outperforms the other existing approaches in terms of flexibility, accuracy and comprehensiveness. © 2011 Canadian Society for Chemical Engineering     

Automated targeting for inter-plant water integration

Apart from in-plant water recovery, inter-plant water integration (IPWI) offers another promising mean for the reduction of fresh water and wastewater flowrates for process plants. This paper extends the automated targeting technique that was developed for single water network into IPWI. This optimisation-based technique is based on the concept of pinch analysis, which enables the setting of various network targets prior to detailed design. The automated targeting technique is formulated as a linear programming model for which global optimum is guaranteed. The proposed technique is demonstrated using several industrial and literature examples.     

Optimal design of extractive dividing-wall column using an efficient equation-oriented approach

The extractive dividing-wall column(EDWC)is one of the most efficient technologies for separation of azeotropic or close boiling-point mixtures,but its design is fairly challenging.In this paper we extend the hybrid feasible path optimisation algorithm(Ma Y,McLaughlan M,Zhang N,Li J.Computers&Chemical Engineering,2020,143:107058)for such optimal design.The tolerances-relaxation integration method is refined to allow for long enough integration time that can ensure the solution of the pseudo-transient continuation simulation close to the steady state before the required tolerance is used.To ensure the gradient and Jacobian information available for optimisation,we allow a relaxed tolerance for the simulation in the sensitivity analysis mode when the simulation diverges under small tolerance.In addition,valid lower bounds on purity of the recycled entrainer and the vapour flow rate in column sections are imposed to improve computational efficiency.The computational results demonstrate that the extended hybrid algorithm can achieve better design of the EDWC compared to those in literature.The energy consumption can be reduced by more than 20%compared with existing literature report.In addition,the optimal design of the heat pump assisted EDWC is achieved using the improved hybrid algorithm for the first time.     

Preliminary synthesis of work exchange networks

In many chemical plants such as LNG, refineries, air enrichment, and ammonia compression is a major consumer of energy. In such plants, some process streams may need compression, while others may need expansion. Optimal integration of these streams may yield major savings in energy. In this work, we introduce a work exchanger network synthesis problem that is analogous to the well-known heat exchange network synthesis problem. We model the details of compressor and turbine operating curves to identify high-pressure and low-pressure streams that should be matched for work exchange via compression/turbine stages located on a single shaft. We propose a superstructure for the work exchange network configuration and develop a mixed-integer nonlinear program (MINLP) to minimize the total annualized cost for a constant speed of the single shaft. We use this preliminary model to optimize shaft speed, and demonstrate the benefits of an optimized network via an illustrative case study.