Process Integration Techniques Research Articles

Process Integration Technique for Targeting Carbon Credit Price Subsidy

Mitigating climate change requires a portfolio of strategies and the use of carbon dioxide removal techniques or negative emissions technologies (NETs) will be necessary to achieve to achieve this goal. However, the high implementation costs of advanced NETs lead to expensive carbon credits, hindering their broad acceptance and use. One potential solution involves governmental support through subsidies, aiming to boost the availability of NET-derived carbon credits. This research uses a graphical technique based on an extension of pinch analysis to identify the ideal subsidy level for carbon dioxide removal, taking into account factors such as carbon pricing, supply, and demand. The proposed approach modifies the limiting composite curve (LCC) methodology to accurately determine the optimal subsidy and establish the baseline amount of subsidized carbon dioxide removal needed. The approach enables the convenient and efficient construction of the LCC using a composite table algorithm. To illustrate the proposed methodology, two case studies composed of different NETs and demand sectors are investigated. The results show the most advantageous subsidy levels for these technologies, providing valuable insights to guide policymakers and investors in their decarbonization efforts. This research contributes to the development of effective governance and investment strategies by optimizing NET subsidy allocation. Such optimization is crucial for facilitating the widespread implementation of these technologies, which are in-line with the global efforts to mitigate climate change.

Assessment of renewable energy use in natural gas liquid processing by improved process integration with heat pumps

Decarbonisation of the industrial sector is a crucial objective in new technological developments responding to global challenges. Energy-intensive industry is one of the biggest pollutants and it is mostly supplied by fossil fuels. This paper presents the methodology for the assessment of electrified options for the process industry based on systematic process integration techniques. The graphical representation was used to analyse the physical processes of the industrial unit. The improved heat recovery and electrified utility targeting were performed by using the Grand Composite Curve and analysing the main process streams and distillation column system. The electrified thermal utility system uses electric steam boilers, water coolers, heat pumps, etc. The case study analyses the natural gas liquid processing and assesses electrified thermal utility. The initial process was simulated in a UniSim environment and obtained thermophysical properties of process streams were used for the analysis. The integrated electrified scenario presumes using a low-pressure steam boiler, water coolers, propylene coolers and 3 heat pumps. Heat recovery was increased by 4 times compared to the initial process and 100% electrified thermal utilities were used. The energy cost was reduced by 41% and the carbon dioxide emissions are reduced by 512,778 tons per capita compared to existing process when using renewable energy for electrified utility. The approach can be used for further development of industry decarbonisation options and electricity targeting in process industries.

A multi-objective planning method for multi-energy complementary distributed energy system: Tackling thermal integration and process synergy

This study proposes a multi-objective optimization methodology for planning multi-energy complementary distributed energy systems considering process synergy and thermal integration. The process integration technique is integrated into the Energy Hub model to deal with the multi-process synergy and temporal source-load matching. The system design and dispatch strategy are optimized by an augmented ε-constraint method with three objectives (economics, carbon emission, and fossil fuel consumption), and then the optimal tradeoff solution is identified by the Technique for Order Preference by Similarity to an Ideal Solution. Moreover, a novel multi-energy complementary distributed energy system is developed, which includes comprehensive utilization of solar energy (photovoltaic, photothermal, and thermochemical) and middle-low temperature heat utilization technologies, as well as hybrid energy storage technologies. Finally, a case study located in Beijing is selected as an illustrated example. The obtained single-objective optimization solutions and Pareto optimal solutions are further analyzed and compared in terms of system configuration, hourly/yearly energy balance, and thermal integration condition. The results show that the multi-energy complementary distributed energy system presents an economic benefit (reducing 25% of the annual total cost) compared to a gas turbine-based integrated energy system. Considering thermal integration contributes to 5.13% of the cost reduction. The configuration of the energy storage devices will reduce 18% energy supply cost, 9% fossil fuel consumption, and 42% carbon emission with the storage devices' boundary increase from 2 MWh to 60 MWh. Moreover, the optimal design of the system provides a reference for decision-making and a basis for flexible operation. The annual total cost, carbon emission, and fossil fuel consumption of the optimal solution in the Pareto frontier are 8.19 million CNY, 2.91 kt CO2-eq./year, and 18.4 GWh, respectively.

Energy–Water–Carbon Nexus Study for the Optimal Design of Integrated Energy–Water Systems Considering Process Losses

Integrated energy–water systems have been explored using different process integration techniques considering the energy–water–carbon nexus to minimize the carbon footprint, e.g., pinch analysis techniques (power cascade table, water cascade table, and energy planning pinch diagram). However, the power and water losses while considering the energy–water–carbon nexus have not been explored in detail in the previous works. This work focuses on the modifications of the existing pinch analysis methods for energy–water–carbon nexus study while considering power and water losses, for an optimized energy–water system. Power and water losses should not be neglected in the analysis as they have a significant impact on the carbon emissions and overall capacities of energy and water. The effect of losses on energy storage capacity, outsourced electricity, water supply volume and water storage capacity were evaluated on an industrial case study. Results from the case study demonstrate that, while considering power losses during power allocation can lower storage capacity, it tends to raise the needed outsourced electricity supply. As water supply volume tends to increase, the water storage capacity tends to decline when losses are considered. The results were compared to the data without losses, and it was observed that the storage capacity of energy decreases by 4% while outsourced energy increases by 6%. Water supply volume increases by 20% but water storage capacity decreases by 13.7%. The emissions from energy system remains same while from the water system the emissions rise significantly by 20%. It is expected that consumers that takes power and water losses into account will produce more realistic and reliable energy, water, and carbon reduction targets and prevent under-sizing issues in designing integrated energy–water systems.

Plant-Wide Modeling and Economic Analysis of Monoethylene Glycol Production

Monoethylene glycol (MEG) is used to produce polyester fibers and polyethylene terephthalate resins. It is also utilized in antifreeze, pharmaceuticals, and cosmetics applications. In this research, we consider the development of a novel process plant that produces MEG from ethylene. The proposed ethylene-to-ethylene oxide (EO) plant is integrated with an EO-to-MEG plant to reduce utility costs and recover high-value products. Energy-saving opportunities are analyzed via heat integration tools. Furthermore, a multitube glycol reactor is used in conjunction with a novel MTO catalyst in the ethylene-to-EO reactor. Our results demonstrate that the integrated EO/EG plant produces ethylene glycols with that same purity and product recovery as conventional designs. A comparative economic assessment based on a 200,000 t/y plant indicates that process integration techniques can reduce costs significantly.

A targeting algorithm for segregated heat integrated water allocation network

The exchange of resources is a critical step toward long-term viability and market economic strength. The use of Process Integration (PI) techniques has resulted in significant savings in resources. Industrial processes rely heavily on water and heat as input variables. Simultaneous conservation of heat and water is regarded as heat-integrated water allocation networks (HIWANs) in the PI. HIWAN problems may be identified for multiple zones. This leads to the specific problem known as segregated targeting problems (STPs), which are prevalent in various industries. Segregated targeting is characterised by the existence of multiple zones and a set of internal sources. The objective of this research is to address the HIWAN problem within the framework of STP to minimize heat and water consumption. The model's applicability is demonstrated by two illustrative examples, in which around a 20 to 65% reduction in resource requirements is reported when compared with the non-zonal integrated model.

Segregated Targeting for Resource Conservation with Dedicated Sources for Batch Process

Conversation of natural resources is one of the most important steps towards sustainability and market competitiveness. Process Integration techniques have been successfully applied for conserving natural resources. High value-added products are the best suited in batch processes. The conservation of natural resources in batch processes is an important concern. A segregated targeting problem for the batch process is presented in this paper. This paper is focused on segregated targeting problems for optimal use of resources in the batch process through Pinch Analysis. The segregated targeting problem consists of internal sources, resources, dedicated sources and demands. Resource and dedicated sources of a given zone are used by demands of that zone only for a given period of time. Resources are time-independent and with no flow restrictions. Internal sources are also time-independent. Internal sources can be optimally used by any zones in a given time interval. An algorithm is developed so that internal sources can be used in such a way as to minimize resource requirements. This algorithm can be applicable for both semi-batch and batch processes. The applicability of the proposed algorithm is demonstrated through an illustrative example.

Development of a Web-based Application for Optimal Allocation of COVID-19 Vaccine

The COVID-19 pandemic posed a huge impact to the global economy and on the environment. Recent developments in battling the pandemic include the availability of vaccines for public use. The distribution of vaccines requires systematic planning as supplies to a given region can be limited. Process integration techniques such as mathematical programming can be applied to develop solutions for systematic planning of COVID-19 vaccine distribution. To enable the use of mathematical programs for policymakers, a graphical user interface is needed. In this study, a web-based application (app) for allocating vaccines is presented, utilizing non-linear programs to optimally distribute vaccines to different population groups. Two models are incorporated in the app: (1) a model that minimizes the number of vaccines required to slow down the spread of the disease, i.e., reduce the reproductive number to less than one and (2) a model that determines the optimal allocation at the minimum reproductive number. The optimization models for the app were written in Python using the Pyomo package while the graphical user interface is written in JavaScript with the use of the React library. The optimization models are accessed through an API served using a Python web server utilizing the web framework Flask. A case study is used to illustrate how the models work in the web application.

Further development of the RDRA method for the optimal acquisition of data in process integration retrofit projects

Process Integration techniques are powerful in analysing the energy usage of industrial plants and designing retrofit solutions for increasing their energy efficiency. However they are far from constituting the industrial practice. One primary cause for this is the severe time consumption they entail, especially in acquiring the necessary process data. A recently developed method, the Required Data Reduction Analysis (RDRA), aims at reducing this time consumption. It makes use of uncertainty and sensitivity analysis techniques, together with optimisation tools, in order to systematically identify: (i) a reduced number of process parameters, whose information need to be acquired with high detail, and (ii) the maximum acceptable uncertainty of each of them.The paper presents recent additions to the method, expanding its capabilities and addressing two open questions highlighted in previous work. In particular: (i) three sensitivity analysis techniques are compared, based on computational effort and precision, (ii) a novel algorithm for minimising the number of parameters needing detailed data acquisition is proposed and (iii) the impact of the uncertainties characterisation on the outcome of the analysis is assessed.The results of the analysis considering four different case studies provided evidence that the Standardised Regression Coefficient method for sensitivity analysis should be preferred in the Required Data Reduction Analysis, and that the uncertainty characterisation did not jeopardise the results. Moreover, the proposed minimisation algorithm proved to be effective and fast in reducing the number of parameters. A reduction of 5 to 13 parameters out of 19 to 22 was achieved on the four case studies by requiring 14000 to 22000 model simulations.

Shaving electric bills with renewables? A multi-period pinch-based methodology for energy planning

As the energy demand keeps growing with the world's increasing population, concerns have arisen about the carbon emissions that contribute to critical environmental issues. These environmental concerns drive many nations to commit themselves in pursuing sustainable energy resources. Different process integration techniques have been developed to achieve a viable energy planning sector. In reference to the literature review, the use of time-sliced based models in optimization problems is still sparse. Hence, this paper aims to develop a time-sliced based optimization model that can be integrated into energy integration models. With that, a multi-period pinch-based methodology (targeting, scheduling, and optimization) for electric power systems with the hybridization of renewables and fossil-based energy is proposed. The prospective framework is designed to meet the emissions limit, fulfil energy demand, and minimize the electricity bill. An illustrative case study in Malaysia incorporated with an actual billing system is used to demonstrate the effectiveness of the proposed framework. The results show that it is capable of reducing the total electricity bill by 35% and achieving a 71% reduction of emissions by using solar PV as the renewables.

A New Algorithm for the Design of Site Utility for Combined Production of Power, Freshwater, and Steam in Process Industries

Abstract Site utility, without a doubt, is one of the major units in process industries that consumed a lot of fossil fuels and significantly emitted emission pollution. In this paper, a systematic procedure was proposed to optimize the utility system's design and integration based on a targeting approach as process integration technique, exergetic, exergoeconomic, exergoenvironmental analysis associated with life cycle assessment (LCA), and multi-objective optimization through water cycle and genetic algorithms. Total site analysis was performed to provide an essential understanding of the equipment's characteristics and interactions in the site utility system. It also aims for power production and the temperature of the boiler and each steam level with acceptable accuracy. Furthermore, the exergetic, exergoeconomic, and exergoenvironmental analyses were presented to declare the effects of irreversibility, economic, and environmental impacts on the system. In this paper, to show the proposed method's applicability, the optimal design of a site utility associated with a petrochemical complex has been considered. First, the optimal design is performed based on minimization of total annualized costs (TAC) as one-objective function through star software, genetic algorithm (GA), water cycle algorithm (WCA), proposed GA, and proposed WCA method. In the next phase, the optimal design is done based on MOGA, MOWCA, proposed MOGA, and proposed MOWCA methods based on maximum exergetic efficiency, and freshwater production, and minimization of exergetic cost, and total environmental exergetic impact. Results show by using the new procedure, the optimum solution has been achieved by a significant reduction of computational time.

Simultaneous design and integration of multiple processes for eco-industrial park development

Process integration techniques have been well established in various areas, which include energy recovery, in-plant material recovery, industrial symbiosis, energy planning, financial management, etc. Such techniques are widely applied in the research community and industrial applications. Synthesising and designing an eco-industrial park via process integration techniques is recognised as one of the most effective strategies to promote sustainable industrial systems. Feasible operating range analysis has been introduced to evaluate and determine the true operating potential of an eco-industrial park coalition without experiencing design and performance limitations. Such tool also acts as a comprehensive decision-making tool for designers to evaluate the performance of an integrated process at different operational states. In this perspective, a novel mixed-integer linear programming model is presented in this work for simultaneous design and integration of multiple processes to form an eco-industrial park. The true potential and performance of the eco-industrial park developed can be assessed at different operational states. To illustrate the proposed approach, an industrial case study on design of eco-industrial park in oil palm industry, which consists of palm oil mill, integrated biogas and wastewater treatment system, palm-based biorefinery, and combined heat and power system, is solved and presented.

Improving the Energy Efficiency for Propane Recovery from Natural Gas using Pinch Technology: A Case Study

Process integration (PI) techniques is an efficient approach to increase the profitability due to reduction in energy, water and raw materials consumption, reduction in greenhouse gas (GHG) emissions, and in waste generation. The PI method, pinch technology is certainly the most widely used in industrial processes. When planning a new plant or revamping an existing plant it is very important to understand and select the right process to minimize capital and operating costs. This research was directed to investigate the reduction of energy consumption in propane recovery units that process natural gas produced from wells existing in the Egyptian western desert fields. The first step was process simulation of the existing gas processing plant using AspenHysys8.3 steady state process simulation program. Next, pinch technology has been adopted in order to achieve minimum hot and cold utilities and save capital cost of the process. Target utilities were calculated using pinch analysis in the Aspen energy analyzer program. Modifications in heat exchanger network could result in savings of 8.3% in hot utility, 6.5% in cold utility of the existing plant and of 46.7% in capital cost for a grass root plant.

A method for faster application of process integration techniques in retrofit situations

Numerous process integration techniques were proved to be highly effective for identifying and estimating potential energy savings in the industry. However, they require high time and effort to collect and analyse process data. As a result, they do not constitute the common practice in the industry and opportunities for increasing the energy efficiency of industrial processes are missed.The paper presents a method, termed the “Energy-Saving Decomposition”, which is based on Process Integration techniques. It is intended for expeditiously outlining and promoting energy efficiency in the industry. Two screening tools, based on mathematical criteria and engineering experience, are employed for reducing the problem dimension before applying conventional design procedures. The first step disregards streams based on their contribution to the overall energy-saving potential, calculated utilising a novel energy-saving decomposition technique. The most promising network is then selected based on its energy-saving potential and size. The second step reduces the problem complexity further, employing economic considerations.This novel method was exemplified by application to a dairy factory: the outcomes and the method itself were compared to conventional Pinch Analysis techniques. The results showed that the developed method can simplify and reduce the time consumption of conventional Process Integration methods significantly, while identifying the most encouraging saving opportunities. The automatic algorithm allowed for reducing the problem size from 62 process streams of the existing plant to 22 streams requiring a computational time of only 135 s. The final retrofit design proposed was the same obtained with conventional Pinch Analysis, achieving a 23% reduction in the plant final energy consumption.

An Optimal Water-Waste Nexus for an Eco-Industrial Park

Resource sustainability is a top priority agenda nowadays which is extensively discussed in the circular economy concept. Reduction of water consumption, as well as final waste generation can be achieved by implementation of process integration and optimisation techniques. Promotion of eco-industrial park (EIP) as an option to improve conventional industrial park will enable the symbiotic participation of all parties, including the nearby domestic community. In this paper, a mathematical model is developed to maximise profit generation from simultaneous resource recovery and water integration from the wastewater. The novelty lies on consideration of multiples sources from industrial and domestic streams, while performing simultaneous regeneration, recycle, and reuse of water and resource recovery works. A superstructure and the associated mathematical equations are developed. Five types of contaminants i.e Chemical Oxygen Demand (COD), Total Dissolved Solid (TDS), Total Suspended Solid (TSS), Chromium (Cr), and Zinc (Zn) will be considered in the model. Generic Algorithm Modelling System (GAMS) is used as the optimisation tool. The case study result shows that a total annual profit of 200,788 USD/y could be generated by the centralized wastewater utility service provider and the payback period is less than 3 y. As a result, 37 % of freshwater could be minimized and 0.02 dry t/h of waste metal precipitate can be recovered from the wastewater. The demand side is also economically benefitted as the cost of supplied water is 10 % lower than the typical cost. The model provides insight on how the domestic and industrial sources can be symbiotically integrated, while retaining economic benefits to the centralized wastewater utility service provider and the demands.

Process integration for emerging challenges: optimal allocation of antivirals under resource constraints.

The global scientific community has intensified efforts to develop, test, and commercialize pharmaceutical products to deal with the COVID-19 pandemic. Trials for both antivirals and vaccines are in progress; candidates include existing repurposed drugs that were originally developed for other ailments. Once these are shown to be effective, their production will need to be ramped up rapidly to keep pace with the growing demand as the pandemic progresses. It is highly likely that the drugs will be in short supply in the interim, which leaves policymakers and medical personnel with the difficult task of determining how to allocate them. Under such conditions, mathematical models can provide valuable decision support. In particular, useful models can be derived from process integration techniques that deal with tight resource constraints. In this paper, a linear programming model is developed to determine the optimal allocation of COVID-19 drugs that minimizes patient fatalities, taking into account additional hospital capacity constraints. Two hypothetical case studies are solved to illustrate the computational capability of the model, which can generate an allocation plan with outcomes that are superior to simple ad hoc allocation.Graphic abstract

Sequential Thermal and Power Integration for Locally Integrated Energy Sector

Energy Efficiency is aligned with the United Nation Sustainable Development Goal for ensuring access to affordable, reliable, sustainable and modern energy for all. Locally Integrated Energy Sector (LIES) concept is introduced for energy conservation between industrial, service and residential sectors. The LIES concept extended the Process Integration technique for energy recovery between multiple process plants through the utility system, known as Total Site Heat Integration (TSHI). However, the development of LIES techniques is divided into two main directions, which are heat and power energy integration. This paper introduces a sequential approach for integrating the heat and electricity system in a LIES. The optimization is done based on time frame, which Time Slices (TSLs) are identified based on drastic changes in heat and electricity supply and demand. The heat system is first analysed by TSHI techniques, which the heat excess and demand are determined. The excess and demand is then used for cogeneration opportunities estimation, which the backpressure and condensing turbine are used. The potential power generation estimated then included to analyse the electricity system using Power Pinch Analysis tools. The use of heat and power storage system are also included in the study, for assessing its impact on the LIES’s energy efficiency. The study considered on- and off-grid power supply system to satisfy the power demand of the system. This proposed heat and power optimisation framework aims to select a system configuration with minimal energy cost.

Algebraic and Automated Targeting Techniques for Resource Allocation Problems in Production Planning

Optimum planning of resources is crucial in ensuring business sustainability. In the past decade, several graphical planning tools have been proposed based on process integration techniques for the optimum allocation of production resources such as equipment, financial, and human resources. These graphical tools provide useful insights for production planners in allocating resources to fulfill production needs. Nevertheless, graphical tools suffer from inaccuracy problems, in addition to being cumbersome. In this work, algebraic and automated targeting techniques are proposed to overcome the above limitations. The algebraic technique proposed is the numerical equivalent to the graphical targeting tool and can be implemented in spreadsheet software. The automated technique, on the other hand, is conceptually similar to the algebraic technique, but is implemented on an optimization platform. Apart from performing cost optimization, the automated technique can be extended to account for availability and pace of the production resources, which is the main novelty of this work. Doing these would involve tedious iterative steps with both graphical and algebraic techniques. Five examples involving different production resource allocations are solved to demonstrate the newly proposed techniques.

Evaluation of CCS Networks Based on Pinch Design Method in the Central Part of Indonesia

At least for two decades, various techniques have been developed to solve the greenhouse gas emissions problem. The carbon capture and storage (CCS) technology is the main solution to reduce carbon dioxide emissions from the industrial sector and power plant. CCS involves the capture of CO2 emissions from an exhaust gas, transporting and storing in geological storage. All of these CCS activities give several planning problems related to geographical conditions that may be an archipelago country, a considerable distance between the CO2 sources and sinks, and the difference in time of CO2 capturing and injecting to storage. The process integration technique by pinch design method can be used for CCS networks. This paper presents an application of pinch design method for CCS networks in central parts of Indonesia. The integration of carbon incentive and carbon tax is proposed to evaluate the value of CCS networks. The effect of time difference between sources and sinks on the amount of CO2 uncaptured was considered to assess the sensitivity of CCS project’s value. The results showed that the combination of pinch design method with the carbon trading and carbon tax provided a potential method to assess the effectiveness of CCS networks.

An integrated approach for sustainability assessment with hybrid AHP-LCA-PI techniques for chitosan-based TiO2 nanotubes production

Designing a sustainable process requires the aid of systematic multivariate assessment method that considers the dimensions of economic, social and environmental impact. This work presents a sustainability assessment framework for the commercial production of chitosan-based titanium dioxide (TiO2) nanotubes using a hybrid method consisting of analytical hierarchy process (AHP), life cycle assessment (LCA) and process integration (PI) techniques. Despite the attractive financial return of the case study as mentioned, its adverse environmental impacts pose challenges to commercialisation due to large consumption of chemicals and waste discharge. Hence, five production alternatives with resource conservation options were evaluated. AHP was adopted as a multiple criteria decision-making tool considering all three dimensions of sustainability; the latter include capital and operating costs, handling risk, alongside with environmental criteria, namely cumulative energy demand (CED), global warming potential (GWP) and water depletion (WD). The selected alternatives were validated through experiment works. Reutilisation of calcium chloride was determined to be the preferred configuration as it fulfilled all three sustainability dimensions, as compared to other alternatives.