Complex Heat Exchanger Network Research Articles

Integrating reaction pathways and downstream separation network for optimal sustainable process route selection

Reducing the environmental impact of chemical production has become a critical objective due to carbon emission regulations and the challenges the carbon market poses. Downstream separation network optimization, which can improve process sustainability by using complex heat exchanger networks, applying advanced separation techniques, optimizing the design/operating parameters, etc., has been researched for many years. However, most optimization work focuses solely on downstream separation sections without considering the selection of raw materials and different reaction pathways. This work aims to develop a mixed integer nonlinear programming (MINLP) optimization model, which integrates reaction pathway selection and downstream separation optimization, to select the optimal sustainable process route for utilizing raw materials or producing products. The objective is to maximize/minimize the process profit/cost. Decision variables such as binary variables, which represent the selection of separation task, key component, heating utility, and continuous variables, which influence the separation mass/energy balance, are considered. By giving parameters like reaction conversion rate, selectivity, and raw material/product price, this optimization model can identify the optimal process route for producing a target product or utilizing a raw material. The optimization model was applied to two case studies: one-step isobutylene and methanol utilization and two-step 1,4-butanediol (BDO) production. The process routes, using isobutylene for pivalic acid production and methanol for gasoline production, have the highest process profit per carbon emission. And the process route, which uses acetylene for BDO production, leads to minimum process cost.

Process Simulations of High-Purity and Renewable Clean H2 Production by Sorption Enhanced Steam Reforming of Biogas

Renewable clean H2 has a very promising potential for the decarbonization of energy systems. Sorption enhanced steam reforming (SESR) is a novel process that combines the steam reforming reaction and the simultaneous CO2 removal by a solid sorbent, such as CaO, which significantly enhances hydrogen generation, enabling high-purity H2 production. The CO2 sorption reaction (carbonation) is exothermic, but the sorbent regeneration by calcination is highly endothermic, which requires extra energy. Biogas is one of the available carbon-neutral renewable H2 production sources. It can be especially relevant for the energy integration of the SESR process since, due to the exothermic sorption reaction, the CO2 contained in the biogas provides extra heat to the system, which can help to balance the energy requirements of the process. This work studies different process configurations for the energy integration of the SESR process of biogas for high-purity renewable H2 production: (1) SESR with sorbent regeneration using a portion of the produced H2 (SESR+REG_H2), (2) SESR with sorbent regeneration using biogas (SESR+REG_BG), and (3) SESR with sorbent regeneration using biogas and adding a pressure swing adsorption (PSA) unit for hydrogen purification (SESR+REG_BG+PSA). When using biogas as fuel (Cases 2 and 3), these configurations were studied using air and oxy-fuel combustion atmospheres in the sorbent regeneration step, resulting in five case studies. A thermodynamic approach for process modeling can provide the optimal process operating conditions and configurations that maximize the energy efficiency of the process, which are the basis for subsequent optimization of the process at the practical level needed to scale up this technology. For this purpose, process simulations were performed using a steady-state plant model developed in Aspen Plus, incorporating a complex heat exchanger network (HEN) to optimize heat integration. A comprehensive parametric study assessed the effects of biogas composition, temperature, pressure, and steam to methane (S/CH4) ratio on the process performance represented by the selected key performance indicators, i.e., H2 purity, H2 yield, CH4 conversion, cold gas efficiency (CGE), net efficiency (NE), fuel consumption for the sorbent regeneration step, and CO2 capture efficiency. H2 with a purity of 98.5 vol % and a CGE of 75.7% with zero carbon emissions can be achieved. When adding a PSA unit, nearly 100% H2 purity and CO2 capture efficiency were achieved with a CGE of 77.3%. The use of oxy-fuel combustion during regeneration lowered the net efficiency of the process by 2.3% points (since it requires an air separation unit) but allowed the process to achieve negative carbon emissions.

Polygon generation and video-to-video translation for time-series prediction

This paper proposes an innovative method for time-series prediction in energy-intensive industrial systems characterized by highly dynamic non-linear operations. The proposed method can capture the true distributions of the inputs and outputs of such systems and map these distributions using polygon generation and video-to-video translation techniques. More specifically, the time-series data are represented as polygon streams (videos), then the video-to-video translation is used to transform the input polygon streams into the output ones. This transformation is tuned based on a model trustworthiness metric for optimal video synthesis. Finally, an image processing procedure is used for mapping the output polygon streams back to time-series outputs. The proposed method is based on cycle-consistent generative adversarial networks as an unsupervised approach. This does not need the heavy involvement of the human expert who devotes much effort to labeling the complex industrial data. The performance of the proposed method was validated successfully using a challenging industrial dataset collected from a complex heat exchanger network in a Canadian pulp mill. The results obtained using the proposed method demonstrate better performance than other comparable time-series prediction models. This allows process operators to accurately monitor process key performance indicators (KPIs) and to achieve a more energy-efficient operation.

Solving complex retrofit problems using constraints and bridge analysis

The aim of this paper is to conduct retrofit analysis of large, complex industrial Heat Exchanger Networks using an automated Bridge Analysis. Large, complex networks have many different possible retrofit designs, or Retrofit Bridges, which requires both computational effort and user effort to evaluate. In this paper, constraints relating to the thermodynamic and economic performance of a retrofit design are proposed and applied to significantly reduce Retrofit Bridge options to a smaller, manageable number of design options. These constraints relate to capital costs, payback period, piping, and plant layout. The method is demonstrated with a Kraft pulp mill case study. The Kraft pulp mill currently has 54 heat exchangers and 73 hot and cold streams. Without constraints, the number of possible Retrofit Bridges is 1 x 1020. After applying the constraints, this number is reduced to 15. The remaining Retrofit Bridges are considered to provide high thermodynamic and economic benefit and can be more easily assessed for the best projects. The use of constraints has allowed the complex case study to be solved quickly, and a single design can be selected for further development. The suggested design reduces the utility consumption by 9.2 MW and has an annual Total Retrofit Profit of NZD 2,140,000, requiring a single new exchanger.

A simple method for estimating the irreversibly in heat exchanger networks

This article presented a simplified method for quick estimating exergy destruction and irreversibility distribution ratio (φ) in a complex Heat Exchanger Network (HEN) of a large natural gas refinery in South Pars Gas Field located in the Persian Gulf. By the presented method, the designing of the HEN isn't required and the only necessary data are the temperatures and thermo-physical properties of the fluids at the inlets and outlets of the HEN. The equation of exergy destruction for the HEN was developed and the model was adapted to estimate the contributions of heat transfer and pressure drops due to fluid friction, as the two major causes of irreversibility in the HEN. The irreversibility factors were compared with the results obtained by conventional irreversibility analysis, i.e. considering irreversibility analysis of all individual heat exchangers running in the HEN. By comparison of the results of the two methods, it was shown that the values and trends of the irreversibility factors estimated by the two methods were approximately the same. By this procedure, it is possible to estimate the irreversibility distribution ratio in any HEN very quickly, especially in early stages of the thermal system designs, without solving very complex mathematical relations.

Design and control of a pressure-swing distillation process with vapor recompression

Pressure-swing distillation is widely used to separate minimum-boiling azeotropes when the azeotropic composition has significant pressure dependence. The two columns operate at different pressures with distillate streams having compositions close to their respective azeotropes. Heat integration is typically used since column temperatures are sufficiently different to permit heat transfer.A novel modification to achieve process intensification has recently been proposed that uses vapor recompression on both columns. The study developed a complex heat exchanger network along with the design of the two columns. Dynamic controllability was not studied.The purpose of this paper is to develop a robust control structure for this process. A novel control scheme features the flowrate of the distillate recycle from the high-pressure column as the throughput manipulator with the fresh feed brought in on level control.

On the use of process integration techniques to generate optimal steam cycle configurations for the power plant industry.

The integration of steam cycles in the power plant industry aims at optimizing the conversion of the available heat into mechanical power. The proposed method uses process integration techniques and a multi-objective optimisation procedure to generate optimal steam cycle configurations which can be ordered by complexity-costs and efficiency. The interest of this methods is to allow the integration of complex heat exchanger network layout, providing systematically alternative arrangements using an effective solving method.

Optimal design of the structure and settings of nuclear HTR thermodynamic cycles

A thermal integration method has been used by Framatome-ANP since 2001 in order to optimize thermodynamic cycles (cogeneration and combined cycles) coupled to new nuclear high temperature reactors. This method allows the design of complex thermodynamic cycles that comply to a large number of industrial constraints, without any a priori assumption on the structure of the internal heat exchanger network. This paper briefly recalls the principles of the method and shows how accurate and rigorous exergy analyses can be carried out quite easily in an industrial context. It details on an example how industrial constraints and thermodynamical considerations interact to lead to an optimal cycle structure and settings. The efficiencies obtained are presented and discussed. In particular we discuss what we mean by optimal design. It is shown that this method is well suited to build optimal complex heat exchanger networks. The differences with other methods like the thermoeconomic ones are also briefly discussed.

The optimal manipulation of cooling water flow rates in a heat exchanger network

In a large, complex heat exchanger network, cooling water flow rates are manipulated by adjusting the valves located at the rear of each heat exchanger. Since the heat exchangers are connected in a network, the change of the cooling water flow rate in a heat exchanger by adjusting the valve bring about the changes of the cooling water flow rates in the other heat exchangers. The manipulation techniques are required to operate cooling water flows efficiently. This paper presents the analysis and the manipulation method of the cooling water flow rates at all heat exchangers in a network simultaneously. A nonlinear programming (NLP) formulation is proposed to determine the optimal adjustment of the valves for the required flow rates of the cooling water in the heat exchangers. Solution of this formulation is obtained with a commercial NLP solver (GAMS/MINOS).

Optimal Energy and Cleaning Management in Heat Exchanger Networks Under Fouling

This paper addresses the problem of cyclic cleaning and energy scheduling in special classes of heat exchanger networks (HENs). A salient characteristic of this problem is that the performance of each heat exchanger decreases with time and can then be restored to its initial state by performing cleaning operations. Due to the cyclic nature of the schedule, some operations may span successive cycles (wrap-around) which is taken into account in the mathematical model. A tight mixed integer linear programming (MILP) model is presented which is solved to global optimality. A detailed objective function is used to account for cleaning cost and energy requirements. The formulations can model serial and parallel HENs, as well as network arrangements arising from the combination of these basic cases. The optimization algorithm determines simultaneously: (i) the number of cleaning operations required along with their corresponding timings and (ii) the optimal utility utilization profile over time. A complex heat exchanger network example is presented to illustrate the applicability of the proposed model.

Optimal Cleaning Policies in Heat Exchanger Networks under Rapid Fouling

This paper addresses the problem of short-term cleaning scheduling in a special class of heat-exchanger networks (HENs). A salient characteristic of this problem is that the performance of each heat exchanger decreases with time and can then be restored to its initial state by performing cleaning operations. Because of its practical importance, a specific problem has been considered here involving decaying equipment performance due to milk fouling. A mixed-integer nonlinear-programming (MINLP) model is first presented incorporating general fouling profiles. This model is then linearized to a tight mixed-integer linear-programming (MILP) model which can be solved to global optimality. A detailed objective function is used to account for cleaning cost and energy requirements. The formulations can model serial and parallel HENs as well as network arrangements arising from the combination of these basic cases. The optimization algorithm determines simultaneously: (i) the number of cleaning operation tasks required along with their corresponding timings and (ii) the optimal utility utilization profile over time. A number of complex heat-exchanger networks examples are presented to illustrate the applicability of the proposed models together with comparative performance results between the MINLP and MILP models.

Optimal cyclic cleaning scheduling in heat exchanger networks under fouling

This work addresses the problem of cyclic cleaning scheduling in heat exchanger networks (HENs). A salient characteristic of this problem is that the performance of each heat exchanger decreases with time which can then be restored to its initial state by performing cleaning operations. Due to the cyclic nature of the schedule, some operations may span successive cycles (wrap-around) which should be taken into account in the mathematical models. A tight mixed integer linear programming (MILP) model is proposed minimising cleaning cost and energy requirements. A complex heat exchanger network example is presented to illustrate the applicability of the proposed model.