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Development of a Scalable and Comprehensive Infrastructure Model for Carbon Dioxide Utilization and Disposal
Abstract
Much of the previous research on carbon capture and storage (CCS) has focused on individual technologies for disposing of CO2, such as capture, storage, sequestration, or transport. Moreover, recent research work considers utilization of CO2 as fuels, chemicals, or nutrients for bioreactors. To efficiently manage CO2 and the economic benefits achieved by this process, the CO2 transport and processing infrastructure supporting CCS will have to be constructed at a macro-scale. This paper introduces a scalable and comprehensive infrastructure model for CO2 utilization and disposal that generates an integrated, profit-maximizing CCS system. The proposed model determines where and how much CO2 to capture, store, transport, utilize or sequester to maximize total annual profit while meeting the CO2 mitigation target. The applicability of the proposed model is demonstrated using a case study for treating CO2 emitted by an industrial complex on the eastern coast of Korea in 2020. The results may be important in systematic planning of a CCS infrastructure and in assisting national and international policy makers to determine investment strategies for developing CCS infrastructures.
... However, many industrial processes such as steel, ethylene, or cement production, which are difficult to make carbon neutral, could offer higher value for the captured CO 2 [10]. Previous studies have also demonstrated that models can be used to cover various scales [11][12][13]. Most importantly, this approach helps in assessing the effects of regional variation in CO 2 sources. ...
... Hasan et al. [13] presented a minimum-cost supply chain network for CCUS, focusing on enhanced oil recovery as the available utilization path of CO 2 . Han and Lee [12] used a scalable and stochastic infrastructure model to financially optimize carbon sequestration, utilization, storage, and transportation with respect to a specific climate goal for the eastern part of South Korea. [15,16]. ...
... Transport costs for truck and rail transport are calculated using the method described by Han and Lee [12], which considers the costs of investment, fuel, labor, maintenance, and general expenses. To calculate the costs, the number of required vehicles needs to be known. ...
Synthetic hydrocarbons can be produced sustainably with power-to-gas processes, resulting in a net reduction of greenhouse gas emissions due to the substitution of conventional natural gas and other fossil fuels with carbon-neutral alternatives. Acquisition of the for the synthetic fuel production can be implemented in multiple ways. This work introduces a node-based model to assess different implementation strategies of utilization systems, taking into account temporal effects, regional variation, and economies of scale for capture. Intermediate storage volumes, capture costs, transport quantities, and other relevant infrastructural aspects of the CCU system can be estimated with the model. Finland is used as a case study, focusing specifically on the national and regional scale. capture costs are significant, being nearly four times larger than the cost of storage in the baseline scenario (354 M€, 85 M€). sources with smaller annual emissions increases capture costs by 14% compared to baseline. This increase in cost is comparable to the cost of transporting over a quarter of all captured to off-site processing (varying distance, 100–400 km). Seasonal storage of is found to be beneficial for the cost-efficient production of synthetic fuels, owing to the temporal disparity between emissions and utilization, as well as the overall cost structure of the components. Five key decision categories are proposed for a carbon utilization system: scale, type, units, location, and technological decisions. These may be applied to describe any carbon utilization system, helping to form a more comprehensive picture of a future energy system, where carbon is widely used as a raw material.
... Furthermore, few CO 2 point sources are located so that ship transport could be applied without first having to transport the CO 2 to a suitable harbour (Kjärstad et al., 2016;Serpa et al., 2011). Road transport could be viable primarily for demonstration sites or other small facilities with annual transport quantities below 100 ktCO 2 / a and distances less than 250 km (Han and Lee, 2011). Rail transport could potentially be used for distances and quantities beyond that (Han and Lee, 2011), if the rail network already exists and has suitable sites alongside it. ...
... Road transport could be viable primarily for demonstration sites or other small facilities with annual transport quantities below 100 ktCO 2 / a and distances less than 250 km (Han and Lee, 2011). Rail transport could potentially be used for distances and quantities beyond that (Han and Lee, 2011), if the rail network already exists and has suitable sites alongside it. A portion of the liquid CO 2 would vaporize during longer transport and idle time unless the tank is constantly cooled. ...
Defossilisation of the current fossil fuels dominated global energy system is one of the key goals in the upcoming decades to mitigate climate change. Sharp reduction in the costs of solar photovoltaics, wind power, and battery technologies enables a rapid transition of the power and some segments of the transport sectors to sustainable energy resources. However, renewable electricity-based fuels and chemicals are required for the defossilisation of hard-to-abate segments of transport and industry. The global demand for carbon dioxide as raw material for the production of e-fuels and e-chemicals during a global energy transition to 100% renewable energy is analysed in this research. Carbon dioxide capture and utilisation potentials from key industrial point sources, including cement mills, pulp and paper mills, and waste incinerators, are evaluated. According to this study's estimates, the demand for carbon dioxide increases from 0.6 in 2030 to 6.1 gigatonnes in 2050. Key industrial point sources can potentially supply 2.1 gigatonnes of carbon dioxide and thus meet the majority of the demand in the 2030s. By 2050, however, direct air capture is expected to supply the majority of the demand, contributing 3.8 gigatonnes of carbon dioxide annually. Sustainable and unavoidable industrial point sources and direct air capture are vital technologies which may help the world to achieve ambitious climate goals.
... • CO 2 injection at a feasible injection rate without pressurizing the containment system is referred to as injectivity. It is controlled by the porosity, permeability, thickness, and heterogeneity of the formations ( Han et al. 2011). During and after injection, low permeable seals act as a trap for the injected fluid. ...
... The variation of climate has a high influence on all aspects of society and it is recognized as public concern in the United Nations Frame-work Convention on Climate Change (UNFCCC) ( Pires et al. 2011;Han and Lee 2011). In this contest, carbon capture, utilization and storage (CCUS) systems have an important role and researchers worldwide have focused their attention on carbon capture utilization and storage supply chains. ...
Carbon Capture and Storage technique has been recognized as the most effective method of reducing the increasing concentration of carbon dioxide in the atmosphere with successful applications reported by different countries. This chapter gives a deeper insight into the major components of the carbon capture and storage technology as a major mitigation approach implemented in deep geological formations worldwide. The mechanisms, challenges, and issues understood so far linked to this technology are also presented and discussed in detail. It appears that if a carbon capture and storage project can be safely implemented considering all of the precautions mentioned in this chapter, a great step can be taken towards a better future for the next generation.
... At the strategic level, the planning horizon typically spans decades (e.g., up to 2050, or beyond). Some of these models consider only pipelines (e.g., Jones et al., 2022), while others consider a mix of transportation modes (e.g., Han and Lee, 2011). Pipelines play an important role in transporting large volumes of CO 2 , and this study considers solely this transportation mode. ...
... An MIT project developed a cost weighting surface (Dooley et al., 2008), which is prerequisite for the cost distance calculations that form the basis of pipeline routing algorithms. Since then, a proliferation of transport models that utilize geographic optimization methods have emerged including Han and Lee (Han and Lee, 2011), Mendelevitch et al. (Mendelevitch et al., 2010), Kemp and Kasim (Kemp and Sola Kasim, 2010), Morbee et al. (2012), and van den Broek et al.(van den Broek et al., 2010). ...
Carbon capture, utilization and storage (CCUS) may play an important role for China to achieve the goal of carbon neutrality by 2060. It is of practical significance to identify an optimal CCUS transport infrastructure to connect many CO2 emission sources and storage sinks widely scattered across different areas. There is, however, little research on source-sink matching (SSM) for national-scale CCUS involving different emission industries and different types of storage sinks. To analyse wide CCUS implementation under carbon taxes and CO2 pipeline networks across China in the future, this study estimated the storage potential of 214 onshore oilfields, and conducted nationwide SSM in the Chinese Mainland via the improved ChinaCCS decision support system (DSS). It is found that the CO2 storage potential reaches approximately 3.6 Gt when all onshore oilfields are considered for CO2 enhanced oil recovery (EOR), and it reaches approximately 4.6 Gt when all onshore oilfields are regarded as depleted oil reservoirs. In the case of a carbon tax on carbon emissions, a step-like growth in the CO2 capture and storage amount occurs with increasing carbon tax, that is when the carbon tax ranges from 44.12–51.47/t CO2, the CCUS amount rapidly increases, while the CCUS amount remains relatively stable at the other carbon tax levels. When the carbon tax is higher than $51.47/t CO2, all CO2 emission sources fully implement CO2 capture, large complex networks constructed in North, East and Central-South China, where CO2 is sequestered near emission sources. Under the above scenario, the total length of 780 pipelines is 5.03 × 10⁴ km, the average transport distance is 67.85 km, and pipes with diameters of 12 and 16 inches represent the majority. Considering the possibility of implementing CCUS in North, East and South China in the future, it is necessary to further select reasonable CO2 capture sources and storage sinks, while reserving areas for pipeline laying.
... Although the majority of SimCCS case studies have at least included CO2 storage in deep saline aquifers, other utilization options have also been applied, including CO2-enhanced oil recovery (CO2-EOR) reservoirs, (Middleton, 2013;Middleton et al., 2011), hydrocarbon-depleted fractured shales , enhanced coalbed methane (Middleton et al., 2015a), and acid gas reservoirs (Middleton and Brandt, 2013). SimCCS, first published and released in 2009 (Middleton and Bielicki, 2009a, b), has helped inspire a range of related CCS infrastructure optimization frameworks, particularly in Europe and Asia (Han and Lee, 2011;Klokk et al., 2010;Morbee et al., 2012;Prasodjo and Pratson, 2011;Tan et al., 2013;van den Broek et al., 2010). In addition to CCS, SimCCS has also been used as a direct inspiration for other energy optimization modeling, including hydrogen production and transport (Johnson and Ogden, 2012), geothermal energy extraction (Langenfeld and Bielicki, 2016), and optimization of wind farm generation and electricity transmission (Phillips and Middleton, 2012). ...
Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO2 distribution pipelines are selected in a robust and cost-effective manner. Introduced in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO2 source, sink, and transportation data, SimCCS2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is then solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.
... The development of CO 2 capture technology that is low cost, reliable, and environmentally friendly is critical for CCS. [11][12][13] According to the combustion process of fossil fuel use; there are three types of techniques that can be used to capture CO 2 from stationary sources. [14][15][16][17] 1. Postcombustion capture refers to the use of a chemical absorbent agent to separate CO 2 from the flue gas of fossil fuel combustion. ...
Flue gas collection from steam generators and its utilization in enhanced oil recovery (EOR) can reduce CO2 emissions into the atmosphere and improve oil recovery efficiency. Under the environments of flue gas corrosion in oilfields, the effects of corrosion time, temperature, pressure, velocity, and concentrations of O2, SO2, H2O, and NaCl on corrosion rates of steels used for a downhole string were investigated through physical simulation experiments. The corrosion mechanisms were analyzed by component, and the morphology of the corrosion products tested by X‐ray diffraction (XRD) and scanning electron microscopy (SEM). In the gas phase, the corrosion rates of X70, P110, and N80 notably increase with temperature and O2 concentration. The corrosion rates first increase rapidly with pressure from 1.0 to 3.0 MPa and then remain largely stable. Meanwhile, the corrosion rates of X70, P110, and N80 in the liquid phase first increase and then decrease with temperature and reach maximum values at 90°C. The corrosion rates of X70, P110, and N80 increase notably with velocity and the concentrations of O2, SO2, H2O, and NaCl. The corrosion rate of 13Cr is considerably lower than those of N80, P110, and X70, which shows good corrosion resistance performance. To reduce the flue gas corrosion of a downhole string, the relative humidity of the flue gas should be lower than 0.7, the temperature of the flue gas in the wellbore should avoid the range between 80 and 100°C, the excess air coefficient of the boiler should be kept at a reasonable value to reduce the O2 content in the flue gas, and the flue gas should not be coinjected into wellbores with brine. The injection of flue gas is technically feasible considering the corrosion of downhole string.
... For the biomass gasification facility, it is assumed that the efficiency of two involved sub-processes (biomass gasifying and hydrogen production) is 0.675 and 0.56, respectively [32]. Table 3 presents the technical and economic parameters associated with the electrolysis [33] and CO 2 capture [34] facilities. Note that the operating cost in an electrolysis facility for hydrogen production includes only a cost for electricity consumption (i.e., renewable electric power from RES-based facilities) because the cost for water used in the electrolysis is negligible. ...
... Utilizing CO 2 from thermal power plants for EOR was also addressed. A scalable and comprehensive infrastructure model was developed for CO 2 utilization and disposal [29]. A case study was conducted for an industrial complex on the east coast of Korea in 2020. ...
The transition to net-zero or net-negative emission future implies avoidance of CO2 emissions along with other greenhouse gases. Nevertheless, the research community and industry are progressively converging to a conclusion that CO2 sequestration has serious limitations for the value proposition. Alternatively, creating a demand market and a revenue stream for the recovered almost-pure CO2 may prevail over CO2 sequestration option and improve the economic feasibility of carbon capture technologies. As such, research in the carbon management field is seen to be shifting toward CO2 utilization, directly and indirectly, in energy and chemical industries.
This chapter discusses physical and chemical CO2 utilization pathways and investigates
the existing process integration scenarios and the performance assessment benchmarks.
... Huang et al. [144] (d = 143) provided a general review of optimisation methods used for the deployment of CCS power plants, such as energy expansion planning optimisation models, pipeline network planning, source-sink optimisation models, or CO 2 sequestration optimisation models. Other key papers included Han et al. [145] (d = 103), who developed a scalable and comprehensive infrastructure model that generates an integrated, profit-maximising CCS system from capture to storage of CO 2 ; Zhang et al. [146] (d = 99), who provided a mixed integer linear programming (MILP) model for the design of integrated carbon capture, transport, and storage infrastructure using the example of Qatar; Zhang et al. [147] (d = 95), who developed an inexact management model (ICSM) to identify optimal strategies to plan CO 2 capture and sequestration under uncertainty; and Lee et al. [148] (d = 86), who proposed a multi-objective MILP model combined with a life cycle assessment model in order to optimise both cost and environmental impacts. ...
For many years, carbon capture and storage (CCS) has been discussed as a technology that may make a significant contribution to achieving major reductions in greenhouse gas emissions. At present, however, only two large-scale power plants capture a total of 2.4 Mt CO2/a. Several reasons are identified for this mismatch between expectations and realised deployment. Applying bibliographic coupling, the research front of CCS, understood to be published peer-reviewed papers, is explored to scrutinise whether the current research is sufficient to meet these problems. The analysis reveals that research is dominated by technical research (69%). Only 31% of papers address non-technical issues, particularly exploring public perception, policy, and regulation, providing a broader view on CCS implementation on the regional or national level, or using assessment frameworks. This shows that the research is advancing and attempting to meet the outlined problems, which are mainly non-technology related. In addition to strengthening this research, the proportion of papers that adopt a holistic approach may be increased in a bid to meet the challenges involved in transforming a complex energy system. It may also be useful to include a broad variety of stakeholders in research so as to provide a more resilient development of CCS deployment strategies.
... Utilizing of CO2 from thermal power plants for EOR was also addressed. A scalable and comprehensive infrastructure model was developed for CO2 utilization and disposal [135]. A case study was conducted for an industrial complex on the east coast of Korea in 2020. ...
... Carbon capture and storage (CCS) technology offers another method to address this situation, aiming to utilize or remove CO 2 . CCS technologies separate CO 2 from industrial-and energy-related sources, transport them to a storage location and isolate them from the atmosphere for a long period (Han and Lee 2011). CCS is the most promising technology for CO 2 reduction in future, and its contribution to emissions reduction is expected to increase from 3% in 2020 to 10% in 2030 and 19% in 2050, as predicted by the IEA under the scenario of the global temperature rising by 2°C (IEA 2011). ...
In China, carbon capture and storage (CCS) is recognized as one of the most promising technologies through which to achieve a large reduction in CO2 emissions in future. The choice among different CCS technologies is critical for large-scale applications. With the aim of developing instructive policy suggestions for CCS development, this study proposed an interval programming model to select the optimal CCS technology among the different CCS technologies available in China. The analysis results indicate that the selection of CO2 capture technologies should be based on the actual situation of the project and industry being targeted. If the government implements mandatory CO2 emission reductions, storage in deep saline aquifers is the optimal choice for CO2 sequestration when oil prices are low and the number of available CO2 emission permits is large. In contrast, enhanced oil recovery is the optimal choice when oil prices increase and the availability of CO2 emission permits decreases. It is critical that the government reduce the operating cost and the cost of CO2 capture in particular.
... An optimisation model, InfraCCS model, is described by Morbee et al (2012), which minimises the cost of a CO2 transport network at European scale for -2050 issues, including economies of scale, infrastructure ownership and political incentives, are analysed within the existing CO2 transport infrastructure in (Brunsvold et al., 2011). What is more, utilisation and disposal of CO2 is included in a scalable and comprehensive CCS infrastructure model introduced by Han and Lee (2011). Hasan et al. (2014; design a CO2 capture, utilisation and sequestration (CCUS) supply chain network to minimise the cost by selecting the source plants, capture processes, capture materials, CO2 pipelines, locations of utilisation sites and amounts of CO2 storage. ...
Qatar is currently the highest emitter per capita and targets emission reduction by exercising tight controls on gas flaring. In order to limit the emission under allowances, the power plants have two options: investing in carbon capture and storage (CCS) systems or buying carbon credits for the excess emissions above their allowances. However, CCS systems are expensive for installation and operation. In this paper, a mixed integer linear programming (MILP) model is developed for the design of integrated carbon capture, transport and storage infrastructure in Qatar under carbon trading scheme. We first investigate the critical carbon credit prices to decide under which price it is more beneficial to invest on CCS systems or to buy carbon credits via carbon trading. Then the fair design of the CCS infrastructure is obtained under two fairness scenarios: the same saving ratio and the game theory Nash approach. Fair cost distribution among power plants in Qatar is obtained by selecting the CO2 resources (power plants) to be captured with available capture technologies and materials, designing the transportation pipeline network to connect the resources with the sequestration and/or utilisation sites and determining the carbon trading price and amount among power plants. Under different fairness scenarios, the total costs are slightly higher than that from minimising the total cost to obtain the fair cost distribution. Power plants with higher CO2 emissions determine to install CCS system, while other power plants buy the carbon credits from domestic or international market to fulfil their carbon allowance requirements. The future work includes extending the current model by considering power generation distribution and designing the pipeline network with the selection of pump locations and pipe diameters.
... More than 3000 emission points and various alternatives of carbon dioxide capture technologies (absorption-, adsorption-, and membrane-based), utilization (enhanced oil recovery) and sequestration (in saline formations and unmineable coal bed areas) are considered in this study. Han and Lee (2011) worked on carbon dioxide utilization and disposal infrastructure development and its optimization in the case of South Korea. Four different carbon dioxide sources (two fired-power plants, one petroleum refinery, and one iron/steel plant) were targeted. ...
This paper reviews issues and applications for design of sustainable carbon dioxide conversion processes, specifically through chemical conversion, and the integration of the conversion processes with other systems from a process systems engineering (PSE) viewpoint. Systematic and computer-aided methods and tools for reaction network generation, processing route generation, process design/optimization, and sustainability analysis are reviewed with respect to carbon dioxide conversion. Also, the relevant gaps and opportunities are highlighted. In addition, the integration of carbon dioxide conversion processes with other systems including coexisting infrastructure and carbon dioxide sources is described. Then, the importance of PSE based studies for such application is discussed. Finally, some perspectives on the status and future directions of carbon dioxide conversion technology and the development and use of PSE approaches are given.
... Os resultados ótimos foram obtidos em 496 s usando o otimizador XPRESS versão 19.00 em um computador HP Compaq Intel Celeron de 2.4 GHz. Han & Lee (2011) propuseram um MILP para resolver um problema de CCS com algumas variações interessantes sobre os modelos apresentados até então. Nesse caso eles modelaram variáveis de localização diferenciando entre indústria, planta e tipo de produção de cada planta. ...
Neste artigo, analisamos uma estratégia para reduzir as emissões de carbono que combina simultaneamente a criação de políticas de incentivo econômico e o desenvolvimento de uma infraestrutura de rede para captura e sequestro de carbono (CCS). Propomos um modelo de otimização linear inteira mista que considera aspectos técnicos e teóricos e permite analisar simultaneamente os efeitos de estabelecer preços para as emissões de carbono (carbon tax) em conjunto com uma estratégia de implementação de uma rede de supply chain para capturar, transportar e sequestrar CO2 em reservatórios geológicos. Apresentamos resultados para o caso da indústria de cimento do Brasil usando CO2 tax estabelecidas atualmente em outros países.
... Os resultados ótimos foram obtidos em 496 s usando o otimizador XPRESS versão 19.00 em um computador HP Compaq Intel Celeron de 2.4 GHz. Han & Lee (2011) propuseram um MILP para resolver um problema de CCS com algumas variações interessantes sobre os modelos apresentados até então. Nesse caso eles modelaram variáveis de localização diferenciando entre indústria, planta e tipo de produção de cada planta. ...
Neste artigo, analisamos uma estratégia para reduzir as emissões de carbono que combina simultaneamente a criação de políticas de incentivo econômico e o desenvolvimento de uma infraestrutura de rede para captura e sequestro de carbono (CCS). Propomos um modelo de otimização linear inteira mista que considera aspectos técnicos e teóricos e permite analisar simultaneamente os efeitos de estabelecer preços para as emissões de carbono (carbon tax) em conjunto com uma estratégia de implementação de uma rede de supply chain para capturar, transportar e sequestrar CO2 em reservatórios geológicos. Apresentamos resultados para o caso da indústria de cimento do Brasil usando CO2 tax estabelecidas atualmente em outros países.
... A wide range of GIS-optimization models have been developed to solve the problem of designing large-scale CCS infrastructure including Middleton and Bielicki [17], Kemp and Kasim [21], Klokk et al. [12], Mendelevitch et al. [22], van den Broek et al. [16], Poiencot and Brown [23], Li et al. [24], Strachan et al. [25], Han and Lee [26], Morbee et al. [7], and Roddy [27]. The majority of these models are based on a MIP framework. ...
SUMMARY To meet next generation energy needs such as wind- and solar-generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy-related products such as oil, natural gas, electricity, and CO2. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two-stage optimization approach for modeling CCS infrastructure. We show how CO2 pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO2 (up to 45 million tonnes of CO2 per year) from ethylene production facilities and delivers the CO2 to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO2 has great potential to jumpstart commercial-scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Purpose
The Carbon Capture, Utilization and Storage (CCUS) network integrates pipelines, offshore shipping and trucks to transport captured CO2 to utilization facilities or storage sites like depleted oil fields and saline aquifers. However, it faces risks such as natural disasters and storage site and/or utilization facility disruptions, leading to uncertainty. Enhancing resilience in CCUS network design is essential to address these risks. This paper aims to develop a resilient CCUS supply chain network (SCN) that minimizes expected total cost under disruption risks while ensuring the required CO2 emission reduction target is met.
Design/methodology/approach
This paper proposes a novel chance-constrained programming approach with multiple-resilience strategies for optimal designing the resilient CCUS SCN problem under storage site and/or utilization facility disruptions, where the storage site and/or utilization facility capacity loss and the storage site and/or utilization facility fortification cost are assumed as uncertain parameters. The proposed uncertain model is transformed into a tractable deterministic equivalent model.
Findings
A case study from Guangdong Province, China, verifies the effectiveness of the proposed model. The sensitivity analysis examines the effects of the expected values of uncertain parameters on the total SCN cost. The results show that for capacity losses under 50%, the reactive transshipment strategy is more economical, particularly as losses decrease. Over 50%, proactive fortifications are more cost-effective, especially with greater losses.
Originality/value
This paper is the first to introduce two resilience strategies (fortifying storage sites and/or utilization infrastructure and lateral transshipment via offshore vessels) to bolster the CCUS network’s capacity to endure unforeseen disruptions. The two strategies are integrated into the proposed chance-constrained model. Our novel approach could help companies develop effective, sustainable and reliable CCUS networks capable of withstanding unforeseen risks.
The CCUS industry is developing rapidly worldwide, and its projects are gradually transitioning from single-section initiatives to whole-industry applications. Capture targets have expanded from power plants and natural gas processing to include steel, cement, kerosene, fertilizer, and hydrogen production. This paper analyzes CO2 emissions in eight major industries around oil regions in China, including emission factors, emission scale, and the composition and distribution of emission sources. The cost of CO2 sources and CO2-EOR affordable cost limits under different scenarios are calculated for different oil regions. The main influencing factors of the cost are analyzed, and possible ways to fill the cost gap are proposed. This paper also constructs a CO2-EOR strategic planning framework and a mathematical programming model, formulating short-term, mid-term, and long-term strategic plans for CO2-EOR and storage in 10 oil regions.
Background
The need for greenhouse gas abatement measures grows as climate change threatens life on earth. Negative emission technologies, such as carbon capture and utilization (CCU), can reduce emissions from the transport sector, particularly aviation. However, the lack of support and low public acceptance can impact the successful introduction of new technologies. This study analyzes the factors that influence acceptance of the single production steps (capture, purification, conversion, and transport of CO2) of production of CO2-based jet fuels to identify acceptance hot spots and potential roll-out barriers.
Results
In a quantitative survey with n = 543 German respondents, we find that transport of CO2 in comparison with capture, purification, and conversion of CO2 into hydrocarbons is perceived as less acceptable, efficient, and useful, more expensive as well as damaging for the environment and health. Furthermore, product-step specific risk perceptions, as well as benefit and barrier perceptions for CCU mainly predict people’s attitude towards the four production steps. A cluster-analysis revealed two groups, “Approvers” and “Sceptics”, which were characterized by distinctive perception profiles. Further analysis showed that sustainability (e.g., use of renewable energy) and efficiency (e.g., carbon removal and resource use) were of greater importance to Approvers.
Conclusions
The study’s results suggest the need for further research and information provision to enhance public understanding of the technology and its role as a part of circular economy approaches. Risk perceptions play a central role in determining attitudes towards CCU, which should be considered in future studies and communication strategies. The findings can inform policymakers, industry stakeholders, and communication experts working to promote sustainable aviation fuel technologies.
The atmospheric concentration of carbon dioxide (CO2) is gradually rising every year, resulting in the increasing global temperature along with thorny environmental and health issues. Up to now, considerable attention has been focused on the design and expansion of excellent heterogeneous catalysts for chemical transformation of CO2 into high value-added chemicals. Covalent organic frameworks (COFs) and their hybrid materials as a rapidly developing class of porous crystalline materials have been synthesized to capture and utilize CO2 as a carbon resource for multiple chemicals, such as cyclic carbonate, propiolic acid, oxazolidinone, benzimidazole and so on. Herein, we give a comprehensive summary of COFs and their hybrid materials for chemical transformation of CO2 in recent five years. Meanwhile, some representative examples are highlighted and analyzed in detail. Finally, this review also discusses opportunities and challenges in the research area.
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize fossil-based power and industrial sectors and is a bridging technology for a sustainable transition to a net-zero emission energy future. This work provides an overview of process systems engineering (PSE) research challenges, advances, and opportunities for CCUS applications. We review PSE methods, tools and techniques in process modeling, simulation, optimization, control, material screening, strategic planning, and supply chain network design for CO2 management. We also attempt to give a PSE perspective on emerging CCUS research interests in molecular and materials systems engineering, multiscale modeling and optimization, systems design and integration under uncertainty, and the application of intelligent systems. The purpose is not to cover all aspects of PSE research for CCUS but rather to foster discussion by presenting some plausible future directions and ideas.
This paper describes a design and pre-feasibility study of a multi-user intermediate CO2 storage facility in the Grenland region of Norway, considering upstream and downstream issues. The study focuses on the principles for designing and installing a generic hub facility so that the results can be considered at other sites. The pre-feasibility study found that design pressures of 7 and 15 bar are feasible transport conditions; moreover, it showed that economies of scale might reduce the total cost for a CO2 network. It is recognised that cooperation across the chain is crucial in managing impurities due to the likely diverse sources of CO2. An intermediate storage facility can support the continuous supply of CO2 via a pipeline system for reservoir injection, improving the integrity of the injection well and equipment and the reservoir performance. A mixed-integer linear programming optimisation model has been developed for sizing and costing intermediate storage hubs of CO2 in Grenland and shipping connections between them and stationary emitters. The model considers an aggregated flow of 2 million tonnes per annum of CO2 for 30 years. The 7 bar design pressure has shown lower total costs when compared with the 15 bar scenario. This is due to the higher costs for shipping and intermediate storage when operating at higher pressure, which is larger than the cost reduction from liquefying CO2 to a higher pressure and higher temperature than those required for a 7 bar scenario. The estimated levelised costs were 21,6 € tonne⁻¹ at 7 bar pressure and 27,8 € tonne⁻¹ at 15 bar pressure.
In this study, a multi-period model of an organic waste-to-biodiesel phased supply chain network is developed to strategically consider variations in the biodiesel demand and the organic waste usage over a long-term planning interval. The proposed model can facilitate planning to determine the biorefinery location and the amount of biodiesel to produce, transport, or utilize to reduce the total cost of the organic waste-to-biodiesel supply chain network design while meeting the biodiesel demand during each period of the planning interval. The features and capabilities of the model are validated by application of a future organic waste-to-biodiesel supply chain network design in South Korea. The optimization results illustrate that the average total annual cost of the organic waste of biodiesel based on the multi-period model will be US 3.154–3.156/gallon of biodiesel containing 3% butanol derived from organic waste combined with diesel. A small portion (4.9–6.6%) of the total biodiesel demand was produced from organic waste because of low organic waste availability in the existing anaerobic digestion facilities, leading to increasing the outsourcing costs of butanol. The proposed approach will facilitate the strategic development of a sustainable supply chain network for organic waste recycling for material and energy valorization.
Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy.
In this study, a stochastic model for strategic planning of the butyric acid-to-butanol supply chain network (Ba-to-Bu SCN) is developed to consider variations in the butanol (Bu) demand and butyric acid (Ba) supply derived from industrial/municipal waste. The proposed stochastic model can help determine where and how much Ba to process, Bu to produce, and Ba/Bu to transport to minimize the total cost of the Ba-to-Bu SCN design under Ba processing and Bu demand uncertainties. The features and capabilities of the stochastic model are validated and compared to those of the deterministic model by application of the future Ba-to-Bu SCN design for South Korea in 2030. The optimization results illustrate that the expected total cost of Ba-derived Bu by the stochastic model (US 4889.72 thousand per year). The goal of this study is to develop a decision making tool for a stochastic strategic problem to improve bio-economy caused by uncertainties. The proposed approach will help balance cost efficiency with stability in the uncertain future biorefinery infrastructure.
Carbon Capture and Storage (CCS) is an essential technology for CO2 emissions reductions, which will allow us to continue consuming fossil fuels in the short to medium term. In this work, we developed a multiscale modeling and optimization approach that links detailed models of the capture plant, compression train and pipelines with the CO2 supply-chain network model. This was used to find the cost-optimal CO2 network considering a case-study of meeting a national reduction target in the United Arab Emirates that supplies CO2 for EOR activities. The main decision variables were the optimal location and operating conditions of each CO2 capture and compression plant in addition to the topology and sizing of the pipelines while considering the whole-system behaviour. A key result of our study was that the cost-optimal degree of capture should be included as a degree of freedom in the design of CO2 networks and it is a function of several site-specific factors, including exhaust gas characteristics, proximity to transportation networks and adequate geological storage capacity. This conclusion serves to underscore the need to comprehend the science governing the physical behaviour at different scales and the importance of a whole-system analysis of potential CO2 networks.
In the 2016, CO2 emissions in the world was about 32.3 Gt with the combustion of fossil fuel being the highest contributor. A target for the reduction of CO2 emissions of 60% was set in the Paris Agreement. Thereafter, this topic has acquired much importance in the world, especially in recent years. In this context, carbon capture utilization and its storage supply chain is highly considered as a strategic solution, that can solve the problems related to CO2 emissions. In this work, an overview about carbon capture utilization and its storage supply chain is developed. Due to their important environmental role, mathematical models are required for design and optimization. Hierarchical or simultaneous methodology can be used, and one procedure is suggested for minimizing the total cost of supply chain. Following this, equations related to capture and compression costs, transportation costs, utilization and storage costs are revised. This work, in addition, reviews systems for CO2 capture and compression, and options for CO2 utilization and storage. Many work are present in literature regarding this technology, however more studies should be developed on dynamic state considering uncertainties.
This study develops a deterministic model for optimal design of an integrated network to determine the utility supply (US) and CO2 mitigation (CM) systems in consideration of technology to utilize CO2 as a raw material. The objective of the model is to minimize the expected total cost of an integrated network that satisfies US and CM demands of multi-site companies in an industrial complex during a multi-period planning horizon. This model determines the optimal locations and amounts of: (1) the utility (steam) transferred among companies, and (2) CO2 storage (CS) and (3) CO2 utilization (CU) considering CO2 capture (CC) systems. The proposed model is tested by applying it to Yeosu Industrial Complex in Korea. The total cost for the Alternative Model that considers CS and CU systems (US 136.49 × 10⁶/y difference) lower than the Base Model that considers only the CS system (US$ 548.11 × 10⁶/y). The most prominent difference between two models was the variation in the CM system. This study examined whether the variation of the integrated network would be affected by the variety of CM systems, and confirmed that CO2 was supplied to produce maximum biodiesel yield when the CU system was selected. This result would be interested in many researchers to study the supply chain network problem over multi-site and multi-period planning horizon while considering the capability of biodiesel production based on CO2 as a raw material.
This paper introduces a mathematical formulation to identify promising CO2 capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi‐objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO2 emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business‐as‐usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO2‐based product can replace, exists in the country can come into consideration. This systematic identification will assist decision‐making regarding future R&D investment and construction of large‐scale CCU plants.
Secure, sustainable, and cost-effective energy development will be one of the greatest global challenges in coming decades. This development will include an extensive range of energy resources including coal, conventional and unconventional oil and natural gas, wind, solar, biofuels, geothermal, and nuclear. CO2 capture and storage (CCS) infrastructure is a key example; meaningful CCS in the US could involve capturing CO2 from hundreds of CO2 sources, including coal-fired and natural gas power plants, and transporting a volume of CO2 greater than US oil consumption. Here, we highlight breakthroughs and future challenges for CCS infrastructure optimization and modeling. We start with the evolution of CCS infrastructure modeling from early attempts to represent the capture (sources), transport (network), and storage (sinks) of CO2, through to the integration of more advanced spatial optimization (or location-allocation) approaches including mixed integer-linear programming. We then highlight key future challenges and opportunities, including the representation of significant uncertainties throughout the CCS supply chain and the ability to represent policy and business decisions into CCS infrastructure optimization. Finally, we examine the role that next-generation CCS infrastructure modeling can have in wider massive-scale energy network investments.
In this study, a new design for a sustainable energy system was developed by integrating two technology frameworks: the renewable resource-based energy supply and the conventional (fossil fuel) resource-based energy production coupled with carbon capture and sequestration. To achieve this goal, a new superstructure-based optimization model was proposed using mixed-integer linear programming to identify the optimal combination of these technologies that minimizes the total daily cost, subject to various practical and logical constraints. The performance of the proposed model was validated via an application study of the future transportation sector in Korea. By considering six different scenarios that combined varying crude oil/natural gas prices and environmental regulation options, the optimal configuration of the energy supply system was identified, and the major cost drivers and their sensitivities were analyzed. It was shown that conventional resource-based energy production was preferred if crude oil and natural gas prices were low, even though environmental regulation was considered. Environmental regulation caused an increase in the total daily cost by an average of 26.4%, mainly due to CO2 capture cost.
This article examines the interaction between two strategies to reduce carbon dioxide (CO2) emissions to the atmosphere: the imposition of pricing policies on carbon dioxide emissions and the decision on the network infrastructure for carbon dioxide capture and storage (CCS). The uncertainty of the storage capacity of geological reservoirs for sequestering carbon dioxide has been noted as an important issue in the deployment and cost of a CCS infrastructure. To analyse the relationships between these strategies and the uncertainty of the storage capacity of reservoirs, we propose a novel stochastic mixed-integer linear optimisation model. It minimises investment and construction costs and the costs of capture, transport, and storage of CO2 plus the cost of emitting CO2 to the atmosphere. The model considers technical and economic aspects to resolve both CO2 pricing and the design of a supply chain network for capturing, transporting, and sequestering CO2 in geological reservoirs. We present results for a sample case from the Brazilian cement industry using a CO2tax as currently established in other countries. We verify that, while the CO2 tax increases, it also increases the complexity of the pipeline network of the supply chain and the amount of CO2 that is captured and stored.
While carbon capture, utilization and storage (CCUS) is an enabling technology to reduce CO2 emissions from stationary sources, the design and operation of CCUS schemes pose multiscale challenges. Here, we discuss some of the recent process systems engineering (PSE) developments which pertain to CCUS modeling, simulation and optimization at multiple length and time scales. The multiscale nature of CCUS design is highlighted, and various approaches and contributions in the realms of both hierarchical and simultaneous optimization are discussed. Research challenges and future opportunities toward cost-effective CCUS are also discussed.
We present a stochastic decision-making algorithm for the design and operation of a carbon capture and storage (CCS) network; the algorithm incorporates the decision-maker’s tolerance of risk caused by uncertainties. Given a set of available resources to capture, store, and transport CO2, the algorithm provides an optimal plan of the CCS infrastructure and a CCS assessment method, while minimizing annual cost, environmental impact, and risk under uncertainties. The model uses the concept of downside risk to explicitly incorporate the trade-off between risk and either economic or environmental objectives at the decision-making level. A two-phase-two-stage stochastic multi-objective optimization problem (2P2SSMOOP) solving approach is implemented to consider uncertainty, and the ε-constraint method is used to evaluate the interaction between total annual cost with financial risk and an Eco-indicator 99 score with environmental risk. The environmental impact is measured by Life Cycle Assessment (LCA) considering all contributions made by operation and installation of a CCS infrastructure. A case study of power-plant CO2 emission in Korea is presented to illustrate the application of the proposed modeling and solution method.
This study proposed ship-based carbon capture and storage (CCS) chains with different CO2 liquefaction pressures and compared them in terms of life cycle cost (LCC) to determine the optimal pressure. Seven liquefaction pressures were suggested between the triple point (5.18 bar, −56.6 °C) and the critical point (73.8 bar, 31.1 °C) of CO2 with increments of 10 bar, and the chain was divided into five modules: a liquefaction system, storage tanks, a CO2 carrier, storage tanks in the intermediate terminal and a pumping system. LCC, including capital expenditure (CAPEX) and operational expenditure (OPEX), was used to estimate the CAPEX and OPEX of the five systems of the chain with each of the seven liquefaction pressures. The results showed that the optimal liquefaction pressure was 15 bar (−27 °C), which had an appropriate pressure, temperature, and density. As the liquefaction pressure increased, the costs of the liquefaction and pumping system decreased, and the costs of the storage tanks and CO2 carrier increased. The cost of the liquefaction system was the largest contributor to the LCC, whereas the pumping system accounted for the smallest part. Sensitivity analysis was performed because this study was carried out in an early design stage with data subject to some uncertainty. The results of the sensitivity analysis showed that the optimal pressure was 15 bar without regard to the disposal amount, the distance from source to sink, the uncertainty of an employed methodology, and unit electricity cost.
Recent global warming and climate change are often attributed to anthropogenic CO2 emissions from burning and consumption of fossil fuels. CO2 capture, utilization and sequestration (CCUS) is an enabling technology toward reducing such emissions from stationary sources. However, significant challenges remain to be addressed before CCUS can be deployed at the industrial scale. A major challenge is to reduce the overall cost of CCUS. To this end, we apply a multi-scale approach and provide a comprehensive framework to elucidate materials-centric, process-centric and network-centric understanding toward reducing the overall CCUS cost. At the materials level, a hierarchical in silico screening method is developed to select the candidate adsorbent materials and optimize process conditions in tandem for adsorption-based postcombustion CO2 capture. At the process level, detailed cost-based modeling and optimization of different capture processes are performed, which enable us to develop explicit expressions for the investment and operating costs of capture technologies, and to determine the most cost-effective materials and processes to be used for CO2 capture and compression when addressing diverse emission scenarios. At the network level, we design an optimal nationwide CCUS structure that uses the most appropriate source plants, capture technologies and materials, transportation network, and CO2 utilization and storage sites. We also discuss the factors that affect the CCUS network costs.
Pipeline transport is widely regarded as an advantageous means for CO2 transport in large-scale carbon capture and sequestration (CCS) projects. The deployments of infrastructures for CO2 transport can largely affect the cost and safety of CCS projects. However, the design of pipeline network for CO2 transport could be quite challenging when considering large numbers of CO2 emission sources and potential CO2 geologic sinks. Moreover, many different factors in real-life cases will make the problem subtler, including the overdispersed distribution of sources and sinks, the heterogeneity of different sources and sinks, and the nonlinear thermophysical and hydraulic properties of CO2 flows. Some previous researches have put much effort in studying the design of pipeline network for CO2 transport, and the methodology of superstructure-based modeling has also made a large contribution in this process. A discussion of previous achievements on this problem is provided here in this chapter, which is helpful for future studies.
CO2 capture and storage (CCS) is widely recognized as a climate-change mitigation technology that can significantly sequestrate human-induced CO2 emission. However, there are two main issues that affect the development and deployment of CCS in a region/country: one is the shortage of planning tool for supporting effective decision making regarding timing, sitting and scaling of CCS capture, transport and storage facilities as well as dynamic sink-source matching between capture and storage. The other is uncertainty in technical, economic, political and other dimensions of CCS as the technology is still in early stage of commercialization. Therefore, the objective of this study is to develop an inexact CCS optimization model (ICCSM) for supporting regional carbon capture, transportation and storage planning under interval-format uncertainty with a least-cost strategy. It could address issues related to optimal sink-source matching in a region with multiple capture and storage options. The developed model was then applied to a case study of long term regional CCS planning under uncertainty. To demonstrate its applicability and capability, further scenario analysis indicated that high concentration CO2 from coal-to-chemical/liquids/gas for EOR storage would be early opportunity for CCS in China. In addition, carbon price would be an effective policy instrument for encouraging deployment of CCS. Without sufficient carbon price, it could be difficult for moving CCS from demonstration stage to deployment stage in a short term.
We develop an economic process design for separation of CO2 from the off-gas in ISMPs (iron and steel making plants). Based on the characteristics of the off-gas from which CO2 must be separated, we design two process configurations: PSA (pressure-swing adsorption) and MEA (monoethanolamine)-based chemical absorption. We also develop a simulation model of each process, and perform an economic evaluation of the configurations. Our technical performance analyses show that the CO2 recovery and purity are >90% in the both processes and that highly-concentrated combustible gas (CO and H2) can be obtained as a byproduct. Our economic performance analyses show that the designed processes lead to cost-effective and competitive options ($62/t CO2 separated), compared to the CO2 separation processes used in power plants. Using the combustible gas as a fuel for the boiler of power cycle greatly reduces the cost of CO2 separation in ISMPs.
Currently, climate change and its consequences for the world economy have attracted a lot of multidisciplinary research. In this article, we study the carbon capture and storage (CCS) problem as one of the technological alternatives proposed by the scientific community to mitigate climate change. We present a mixed integer linear programming model to design the infrastructure supply chain network that makes possible the capture and storage of carbon, considering both, the technical and economic aspects involved in the problem. We use the proposed model to study the case of the cement industry in Brazil. Two scenarios of CO2 reductions are considered: 5 Mt and 10 Mt per year. In addition, regarding the required investments to reach the desired reductions, a synthesis of the findings is reported, which includes the reservoirs to be activated as well as the pipeline networks that should be constructed.
We present a multi-scale framework for the optimal design of CO2 capture, utilization, and sequestration (CCUS) supply chain network to minimize the cost while reducing stationary CO2 emissions in the United States. We also design a novel CO2 capture and utilization (CCU) network for economic benefit through utilizing CO2 for enhanced oil recovery. Both the designs of CCUS and CCU supply chain networks are multi-scale problems which require decision making at material, process and supply chain levels. We present a hierarchical and multi-scale framework to design CCUS and CCU supply chain networks with minimum investment, operating and material costs. While doing so, we take into consideration the selection of source plants, capture processes, capture materials, CO2 pipelines, locations of utilization and sequestration sites, and amounts of CO2 storage. Each CO2 capture process is optimized, and the best materials are screened from large pool of candidate materials. Our optimized CCUS supply chain network can reduce 50% of the total stationary CO2 emission in the U.S. at a cost of 9.23 per ton). We have also shown that more than 3% of the total stationary CO2 emissions in the United States can be eliminated through CCU networks at zero net cost. These results highlight both the environmental and economic benefits which can be gained through CCUS and CCU networks. We have designed the CCUS and CCU networks through (i) selecting novel materials and optimized process configurations for CO2 capture, (ii) simultaneous selection of materials and capture technologies, (iii) CO2 capture from diverse emission sources, and (iv) CO2 utilization for enhanced oil recovery. While we demonstrate the CCUS and CCU networks to reduce stationary CO2 emissions and generate profits in the United States, the proposed framework can be applied to other countries and regions as well.
Currently, climate change and its consequences for the world economy have attracted a lot of multidisciplinary research. In this article, we study the carbon capture and storage (CCS) problem as one of the technological alternatives proposed by the scientific community to mitigate climate change. We present a mixed integer linear programming model to design the infrastructure supply chain network that makes possible the capture and storage of carbon, considering both, the technical and economic aspects involved in the problem. We use the proposed model to study the case of the cement industry in Brazil. Two scenarios of CO2 reductions are considered: 5 Mt and 10 Mt per year. In addition, regarding the required investments to reach the desired reductions, a synthesis of the findings is reported, which includes the reservoirs to be activated as well as the pipeline networks that should be constructed.
We design a CO2 Capture, Utilization, and Sequestration (CCUS) supply chain network with minimum cost to reduce stationary CO2 emissions and their adverse environmental impacts in the United States. While doing so, we consider simultaneous selection of source plants, capture technologies, capture materials, CO2 pipelines, locations of utilization and sequestration sites, and amounts of CO2 storage. The CCUS costs include the costs of flue gas dehydration, CO2 capture, compression, transportation and injection, and revenues from CO2 utilization through enhanced oil recovery (CO2-EOR). The dehydration, capture, and compression costs are derived using advanced modeling, simulation, and optimization of leading CO2 capture processes. Our results suggest that it is possible to reduce 50–80% of the current CO2 emissions from the stationary sources at a total annual cost ranging 3.4–3.6 billion of revenue annually through supplying CO2 for CO2-EOR. Overall, the optimal CCUS supply chain network would correspond to a net cost of $35.63–43.44 per ton of CO2 captured and managed. Such a cost-effective network for CO2 management is attained due to (i) using novel materials and process configurations for CO2 capture, (ii) simultaneous selection of materials and capture technologies, (iii) CO2 capture from diverse emission sources, (iv) CO2 utilization for enhanced oil recovery, and (v) nationwide CO2 storage. Results for the regional and statewide (Texas) CCUS are also favorable.
A multiperiod stochastic programming model is developed for planning a carbon capture and storage (CCS) infrastructure including CO2 utilization and disposal in an uncertain environment and with a time-varying investment environment. An inexact two-stage stochastic programming approach is used to analyze the effect of possible uncertainties in product prices, operating costs, and CO2 emissions. The proposed model determines where and how much CO2 to capture, store, transport, utilize, or sequester for the purpose of maximizing the total profit of handling the uncertainty while meeting the CO2 mitigation target during each time period of a given planning interval. The capability of the proposed model to provide correct decisions despite a changing uncertain environment is tested by applying it to designing and operating the future CCS infrastructure on the eastern coast of Korea over a 20-year planning interval (2011–2030).
In this study, a comprehensive infrastructure assessment model for carbon capture and storage (CiamCCS) is developed for (i) planning a carbon capture and storage (CCS) infrastructure that includes CO2 capture, utilization, sequestration and transportation technologies, and for (ii) integrating the major CCS assessment methods, i.e., techno-economic assessment (TEA), environmental assessment (EA), and technical risk assessment (TRA). The model also applies an inexact two-stage stochastic programming approach to consider the effect of every possible uncertainty in input data, including economic profit (i.e., CO2 emission inventories, product prices, operating costs), environmental impact (i.e., environment emission inventories) and technical loss (i.e., technical accident inventories). The proposed model determines where and how much CO2 to capture, transport, sequester, and utilize to achieve an acceptable compromise between profit and the combination of environmental impact and technical loss. To implement this concept, fuzzy multiple objective programming was used to attain a compromise solution among all objectives of the CiamCCS. The capability of CiamCSS is tested by applying it to design and operate a future CCS infrastructure for treating CO2 emitted by burning carbon-based fossil fuels in power plants throughout Korea in 2020. The result helps decision makers to establish an optimal strategy that balances economy, environment, and safety efficiency against stability in an uncertain future CCS infrastructure.
This project developed life-cycle costs for the major technologies and practices under development for COâ storage and sink enhancement. The technologies evaluated included options for storing captured COâ in active oil reservoirs, depleted oil and gas reservoirs, deep aquifers, coal beds, and oceans, as well as the enhancement of carbon sequestration in forests and croplands. The capture costs for a nominal 500 MW{sub e} integrated gasification combined cycle plant from an earlier study were combined with the storage costs from this study to allow comparison among capture and storage approaches as well as sink enhancements.
Atmospheric concentrations of COâ and other greenhouse gases (GHGs) are growing steadily. GHG levels seem likely to grow more quickly in the future as developed countries continue to use large amounts of energy, while developing countries become wealthy enough to afford energy-intensive automobiles, refrigerators, and other appliances (as well as live and work in larger, more comfortable structures). To keep GHGs at manageable levels, large decreases in COâ emissions will be required. Yet analysts understand the difficulty of developing enough zero- and low-carbon-emission technologies to meet the goal of safe GHG stabilization. Carbon sequestration technologies can help bridge this gap. These technologies are only beginning to be developed, but their promise is already evident. In Europe, COâ has been continuously and safely pumped into a below-sea limestone structure for over three years, where it remains. In New Mexico, COâ is being used to drive out natural gas from within unminable coal seams 1,000 meters below the surface, and again, continuously injected COâ has stayed sequestered for over three years, even though the project was designed for natural gas production, not COâ sequestration. These and other beginnings suggest that much COâ could be reused or sequestered over time. However, substantial R and D will be required so that COâ can be captured inexpensively, and then reused or safely sequestered economically. Advanced concepts likely hold great promise as well.
The paper presents an analysis of biomass energy with CO2 capture and storage (BECS) in industrial applications. Sugar cane-based ethanol mills and chemical pulp mills are identified as market niches with promising prospects for BECS. Calculations of CO2 balances of BECS in these applications show that the introduction of CO2 capture and storage in biomass energy systems can significantly increase the systems’ CO2 abatement potentials. CO2 emissions of the total systems are negative. The CO2 reduction potentials of these technologies are discussed in regional and global contexts. An economic assessment of each system is carried out and opportunities for cost-effective technologies for CO2 capture, transportation and storage are identified. Furthermore, potentials for system improvements that could substantially decrease the CO2 abatement cost are addressed.
In the carbon capture and storage (CCS) process, CO2 sources and geologic reservoirs may be widely spatially dispersed and need to be connected through a dedicated CO2 pipeline network. We introduce a scalable infrastructure model for CCS (simCCS) that generates a fully integrated, cost-minimizing CCS system. SimCCS determines where and how much CO2 to capture and store, and where to build and connect pipelines of different sizes, in order to minimize the combined annualized costs of sequestering a given amount of CO2. SimCCS is able to aggregate CO2 flows between sources and reservoirs into trunk pipelines that take advantage of economies of scale. Pipeline construction costs take into account factors including topography and social impacts. SimCCS can be used to calculate the scale of CCS deployment (local, regional, national). SimCCS’ deployment of a realistic, capacitated pipeline network is a major advancement for planning CCS infrastructure. We demonstrate simCCS using a set of 37 CO2 sources and 14 reservoirs for California. The results highlight the importance of systematic planning for CCS infrastructure by examining the sensitivity of CCS infrastructure, as optimized by simCCS, to varying CO2 targets. We finish by identifying critical future research areas for CCS infrastructure.
Due to a heightened interest in technologies to mitigate global climate change, research in the field of carbon capture and storage (CCS) has attracted greater attention in recent years, with the goal of answering the many questions that still remain in this uncertain field. At the top of the list of key issues are CCS costs: costs of carbon dioxide (CO2) capture, compression, transport, storage, and so on. This research report touches upon several of these cost components. It also provides some technical models for determining the engineering and infrastructure requirements of CCS, and describes some correlations for estimating CO2 density and viscosity, both of which are often essential properties for modeling CCS. This report is actually a compilation of three separate research reports and is, therefore, divided into three separate sections. But although each could be considered as a stand-alone research report, they are, in fact, very much related to one other. Section I builds upon some of the knowledge from the latter sections, and Sections II & III can be considered as supplementary to Section I. * Section I: Techno-Economic Models for Carbon Dioxide Compression, Transport, and Storage – This section provides models for estimating the engineering requirements and costs of CCS infrastructure. Some of the models have been adapted from other studies, while others have been expressly developed in this study. * Section II: Simple Correlations for Estimating Carbon Dioxide Density and Viscosity as a Function of Temperature and Pressure – This section describes a set of simple correlations for estimating the density and viscosity of CO2 within the range of operating temperatures and pressures that might be encountered in CCS applications. The correlations are functions of only two input parameters—temperature and pressure—which makes them different from the more complex equation of state computer code-based correlations that sometimes req
In 2005, Korea launched several carbon management R&D projects as one of the governmental global climate change policies, specifically about the CO2 storage in geologic and oceanic reservoirs. CO2 ocean sequestrations have been developed as an effective method to sequester amount capacity of CO2, because the capacity of terrestrial sequestration sites on land is very limited in Korea. However, cost-ineffectiveness has been indicated as one of the key barriers. In this paper, the preliminary evaluation of the technical and economic feasibility by the "Moving Ship" method in Korea is carried out and its prospects are outlined. Also, we try to discuss the issues of elemental technologies and emphasize the necessity of continuing R&D efforts for the effective system development of CO2 ocean sequestration. Copyright © 2007 by The International Society of Offshore and Polar Engineers(ISOPE).
To mitigate the climate change and global warming, various technologies have been internationally proposed for reducing greenhouse gas emissions. Especially, in recent, carbon dioxide capture and storage (CCS) technology is regarded as one of the most promising emission reduction options that be captured from major point sources (eg., power plant) and transported for storage into the marine geological structure such as deep sea saline aquifer. The purpose of this paper is to review the latest progress on the development of technologies for storage in marine geological structure and its perspective in republic of Korea. To develop the technologies for storage in marine geological structure, we carried out relevant R&D project, which cover the initial survey of potentially suitable marine geological structure fur storage site and monitoring of the stored behavior, basic design for transport and storage process including onshore/offshore plant and assessment of potential environmental risk related to storage in geological structure in republic of Korea. By using the results of the present researches, we can contribute to understanding not only how commercial scale (about 1 ) deployment of storage in the marine geological structure of East Sea, Korea, is realized but also how more reliable and safe CCS is achieved. The present study also suggests that it is possible to reduce environmental cost (about 2 trillion Won per year) with developed technology for storage in marine geological structure until 2050.
The offshore gas field named Sleipner—after the mythological horse with eight legs—is situated right in the middle of the North Sea, near the border line between United Kingdom and Norway. The distance from the nearest town on the Norwegian coast, Stavanger, is 240 km. A map is shown in Fig. 1. Together with the even larger Troll gas field further north. Sleipner will produce a larger part of Norway's gas supply to the European Union. It will function as a hub for a number of pipelines transferring this gas from north to south. The field is licenced to the companies Statoil, Esso Norge, Norsk Hydro, Elf Petroleum Norge and TOTAL Norge; with Statoil as field operator. The field was first discovered in 1974 with the gas containing reservoirs laying around 3500 m under the sea bed.
Much of the early research in the hydrogen supply chain area was focused on individual technologies of the supply chain, such as production, storage, or distribution, rather than dealing with the supply chain as a whole. The motivation behind this paper is the need to: (1) design a hydrogen supply chain that integrates the previously mentioned components within a single framework, (2) understand the important trade-offs in such a supply chain, and (3) have a full understanding of the data requirements and uncertainties in such an exercise. Optimization techniques were implemented to develop the hydrogen supply chain for the transport sector, therefore, determining the optimum infrastructural and operational costs. Of course, cost is not likely to be the sole determinant of performance in practice. The network of interest was formulated as a mixed-integer linear programming (MILP) problem. Also, the network is presented as a steady state ‘snapshot’ problem using Great Britain as a backdrop. The model and assumptions presented in this paper reveal that the optimum future hydrogen supply chain might consist of medium-to-large, centralized methane steam reforming plants. The hydrogen produced from these plants will then be delivered as a liquid via tanker trucks and stored in centralized storage facilities.
Studies of CO2 capture and storage (CCS) from coal-fired power plants typically assume a capture efficiency near 90%, although the basis for a particular choice usually is not discussed. Nor do studies systematically explore a range of CO2 capture efficiencies to identify the most cost-effective levels of CO2 control and the key factors that affect such levels. An exploration of these issues is the focus of this paper. As part of the United States Department of Energy's Carbon Sequestration Program, we have developed an integrated modeling framework (called IECM-cs) to evaluate the performance and cost of alternative CCS technologies and power systems in the context of plant-level multipollutant control requirements. This paper uses IECM-cs to identify the most cost-effective level of CO2 control using currently available amine-based CO2 capture technology for PC plants. Two general cases are of interest. First, we examine the effects of systematically increasing the CO2 capture efficiency of an amine-based system for PC applications over a broad range. We report two measures of cost: (i) capital cost and (ii) cost-effectiveness (cost per tonne of CO2 avoided) relative to similar plants without CCS. Second, we examine the cost-effectiveness of plant designs that partially bypass the amine capture unit so as to achieve low to moderate reductions of CO2, but at lower overall cost. Results from these cases are compared to the conventional case of a capture unit treating the entire flue gas stream. In each case, we identify the most cost-effective strategies and the key factors that affect those results.
Introducing hydrogen as the fuel of the future necessitates a comprehensive, widespread supply chain network that is capable of producing, distributing, storing, and dispensing hydrogen to end users. Most of the early attempts to design and model the future hydrogen supply chain (HSC) were either limited to examining an individual component of the supply chain or focused on a predetermined hydrogen pathway. In these studies, a simulation-based approach has commonly been adopted rather than using a mathematical programming-based approach. The work presented here is an extension of an early attempt to design and operate a deterministic, steady-state HSC network using a mathematical modelling approach. In this paper, however, the model is developed to consider the availability of energy sources (i.e. raw materials) and their logistics, as well as the variation of hydrogen demand over a long-term planning horizon leading to phased infrastructure development. The proposed model is formulated as a mixed-integer linear programming (MILP) and solved via a commercial software tool, GAMS. The results show that the optimal design of the future HSC network of Great Britain (GB) starts with small-size plant together with using the hydrogen currently produced by chemical processing plants. As demand grows, more plants of different sizes should be built to meet the demand. The hydrogen produced will be transported using liquid hydrogen trucks and stored in different sizes of storage facilities.
Three different types of membranes were experimentally evaluated for CO2 recovery from blast furnace effluents: semi-commercial adsorption selective carbon membranes, in-house tailored carbon molecular sieving membranes, and fixed site carrier (FSC) membranes with amine groups in the polymer backbone for active transport of CO2. In the single gas experiments the FSC membranes showed superior selectivity for CO2 over the other relevant gases (CO, N2 and H2) and high CO2 permeance (productivity). In addition, it is easy to process and handle, relatively inexpensive to produce and the water in the feed gas is an advantage rather than a problem, since the membrane must be humidified during operation. Based on these experiments a simulation study of a full scale process was performed. The technology showed notable low energy cost, even when converted to the thermal equivalent. Total costs for the CO2 recovery unit (CO2 prepared for pipeline transport) were estimated to be in the range 15.0–17.5 €/tonnes CO2.
Carbon dioxide capture and storage (CCS) involves the capture of CO2 at a large industrial facility, such as a power plant, and its transport to a geological (or other) storage site where CO2 is sequestered. Previous work has identified pipeline transport of liquid CO2 as the most economical method of transport for large volumes of CO2. However, there is little published work on the economics of CO2 pipeline transport. The objective of this paper is to estimate total cost and the cost per tonne of transporting varying amounts of CO2 over a range of distances for different regions of the continental United States. An engineering-economic model of pipeline CO2 transport is developed for this purpose. The model incorporates a probabilistic analysis capability that can be used to quantify the sensitivity of transport cost to variability and uncertainty in the model input parameters. The results of a case study show a pipeline cost of US 0.39 per tonne lower in the Central US and US 2.23 per tonne of CO2 for a 100 km pipeline, and US 4.06 per tonne CO2 for a 200 km pipeline. An illustrative probabilistic analysis assigns uncertainty distributions to the pipeline capacity factor, pipeline inlet pressure, capital recovery factor, annual O&M cost, and escalation factors for capital cost components. The result indicates a 90% probability that the cost per tonne of CO2 is between US 1.03 and US$ 2.63 per tonne of CO2 transported in the Midwest US. In this case, the transport cost is shown to be most sensitive to the pipeline capacity factor and the capital recovery factor. The analytical model elaborated in this paper can be used to estimate pipeline costs for a broad range of potential CCS projects. It can also be used in conjunction with models producing more detailed estimates for specific projects, which requires substantially more information on site-specific factors affecting pipeline routing.
Commercialization of carbon capture and storage from fossil fuelled power plants requires an infrastructure for transportation of the captured carbon dioxide (CO2) from the sources of emission to the storage sites. This paper identifies and analyses different transportation scenarios with respect to costs, capacity, distance, means of transportation and type of storage. The scenario analysis shows that feasible transportation alternatives are pipelines (on and off shore), water carriers (off shore) and combinations of these. Transportation scenarios are given for different transportation capacities ranging from a demonstration plant with an assumed capacity of 200 MWe (1Mt/y of CO2) up to a system of several large 1000 MWe power plants in a coordinated network (40 Mt/y up to 300 Mt/y of CO2). The transportation costs for the demonstration plant scenario range from 1 to 6€/ton of CO2 depending on storage type and means of transportation. The corresponding figure for the coordinated network scenario with off shore storage is around 2€/ton of CO2.
This paper assesses the three leading technologies for capture of CO2 in power generation plants, i.e., post-combustion capture, pre-combustion capture and oxy-fuel combustion. Performance, cost and emissions data for coal and natural gas-fired power plants are presented, based on information from studies carried out recently for the IEA Greenhouse Gas R&D Programme by major engineering contractors and process licensors. Sensitivities to various potentially significant parameters are assessed.
CO2 capture and storage (CCS) is receiving considerable attention as a potential greenhouse gas (GHG) mitigation option for fossil fuel power plants. Cost and performance estimates for CCS are critical factors in energy and policy analysis. CCS cost studies necessarily employ a host of technical and economic assumptions that can dramatically affect results. Thus, particular studies often are of limited value to analysts, researchers, and industry personnel seeking results for alternative cases. In this paper, we use a generalized modeling tool to estimate and compare the emissions, efficiency, resource requirements and current costs of fossil fuel power plants with CCS on a systematic basis. This plant-level analysis explores a broader range of key assumptions than found in recent studies we reviewed for three major plant types: pulverized coal (PC) plants, natural gas combined cycle (NGCC) plants, and integrated gasification combined cycle (IGCC) systems using coal. In particular, we examine the effects of recent increases in capital costs and natural gas prices, as well as effects of differential plant utilization rates, IGCC financing and operating assumptions, variations in plant size, and differences in fuel quality, including bituminous, sub-bituminous and lignite coals. Our results show higher power plant and CCS costs than prior studies as a consequence of recent escalations in capital and operating costs. The broader range of cases also reveals differences not previously reported in the relative costs of PC, NGCC and IGCC plants with and without CCS. While CCS can significantly reduce power plant emissions of CO2 (typically by 85–90%), the impacts of CCS energy requirements on plant-level resource requirements and multi-media environmental emissions also are found to be significant, with increases of approximately 15–30% for current CCS systems. To characterize such impacts, an alternative definition of the “energy penalty” is proposed in lieu of the prevailing use of this term.
This study provides insight into the feasibility of a CO2 trunkline from the Netherlands to the Utsira formation in the Norwegian part of the North Sea, which is a large geological storage reservoir for CO2. The feasibility is investigated in competition with CO2 storage in onshore and near-offshore sinks in the Netherlands. Least-cost modelling with a MARKAL model in combination with ArcGIS was used to assess the cost-effectiveness of the trunkline as part of a Dutch greenhouse gas emission reduction strategy for the Dutch electricity sector and CO2 intensive industry. The results show that under the condition that a CO2 permit price increases from €25 per tCO2 in 2010 to €60 per tCO2 in 2030, and remains at this level up to 2050, CO2 emissions in the Netherlands could reduce with 67% in 2050 compared to 1990, and investment in the Utsira trunkline may be cost-effective from 2020–2030 provided that Belgian and German CO2 is transported and stored via the Netherlands as well. In this case, by 2050 more than 2.1 GtCO2 would have been transported from the Netherlands to the Utsira formation. However, if the Utsira trunkline is not used for transportation of CO2 from Belgium and Germany, it may become cost-effective 10 years later, and less than 1.3 GtCO2 from the Netherlands would have been stored in the Utsira formation by 2050. On the short term, CO2 storage in Dutch fields appears more cost-effective than in the Utsira formation, but as yet there are major uncertainties related to the timing and effective exploitation of the Dutch offshore storage opportunities.
Distillation systems are energy-intensive processes, and consequently contribute significantly to the greenhouse gases emissions (e.g. carbon dioxide (CO2). A simple model for the estimation of CO2 emissions associated with operation of heat-integrated distillation systems as encountered in refineries is introduced. In conjunction with a shortcut distillation model, this model has been used to optimize the process conditions of an existing crude oil atmospheric tower unit aiming at minimization of CO2 emissions. Simulation results indicate that the total CO2 emissions of the existing crude oil unit can be cut down by 22%, just by changing the process conditions accordingly, and that the gain in this respect can be doubled by integrating a gas turbine. In addition, emissions reduction is accompanied by substantial profit increase due to utility saving and/or export.
It has been observed by many people that a striking number of quite diverse mathematical problems can be formulated as problems in integer programming, that is, linear programming problems in which some or all of the variables are required to assume integral values. This fact is rendered quite interesting by recent research on such problems, notably by R. E. Gomory [2, 3], which gives promise of yielding efficient computational techniques for their solution. The present paper provides yet another example of the versatility of integer programming as a mathematical modeling device by representing a generalization of the well-known “Travelling Salesman Problem” in integer programming terms. The authors have developed several such models, of which the one presented here is the most efficient in terms of generality, number of variables, and number of constraints. This model is due to the second author [4] and was presented briefly at the Symposium on Combinatorial Problems held at Princeton University, April 1960, sponsored by SIAM and IBM. The problem treated is: (1) A salesman is required to visit each of n cities, indexed by 1, … , n . He leaves from a “base city” indexed by 0, visits each of the n other cities exactly once, and returns to city 0. During his travels he must return to 0 exactly t times, including his final return (here t may be allowed to vary), and he must visit no more than p cities in one tour. (By a tour we mean a succession of visits to cities without stopping at city 0.) It is required to find such an itinerary which minimizes the total distance traveled by the salesman.
Note that if t is fixed, then for the problem to have a solution we must have tp ≧ n . For t = 1, p ≧ n , we have the standard traveling salesman problem.
Let d ij ( i ≠ j = 0, 1, … , n ) be the distance covered in traveling from city i to city j . The following integer programming problem will be shown to be equivalent to (1): (2) Minimize the linear form ∑ 0≦ i ≠ j ≦ n ∑ d ij x ij over the set determined by the relations ∑ n i =0 i ≠ j x ij = 1 ( j = 1, … , n ) ∑ n j =0 j ≠ i x ij = 1 ( i = 1, … , n ) u i - u j + px ij ≦ p - 1 (1 ≦ i ≠ j ≦ n ) where the x ij are non-negative integers and the u i ( i = 1, …, n ) are arbitrary real numbers. (We shall see that it is permissible to restrict the u i to be non-negative integers as well.)
If t is fixed it is necessary to add the additional relation: ∑ n u =1 x i 0 = t Note that the constraints require that x ij = 0 or 1, so that a natural correspondence between these two problems exists if the x ij are interpreted as follows: The salesman proceeds from city i to city j if and only if x ij = 1. Under this correspondence the form to be minimized in (2) is the total distance to be traveled by the salesman in (1), so the burden of proof is to show that the two feasible sets correspond; i.e., a feasible solution to (2) has x ij which do define a legitimate itinerary in (1), and, conversely a legitimate itinerary in (1) defines x ij , which, together with appropriate u i , satisfy the constraints of (2).
Consider a feasible solution to (2).
The number of returns to city 0 is given by ∑ n i =1 x i 0 . The constraints of the form ∑ x ij = 1, all x ij non-negative integers, represent the conditions that each city (other than zero) is visited exactly once. The u i play a role similar to node potentials in a network and the inequalities involving them serve to eliminate tours that do not begin and end at city 0 and tours that visit more than p cities. Consider any x r 0 r 1 = 1 ( r 1 ≠ 0). There exists a unique r 2 such that x r 1 r 2 = 1. Unless r 2 = 0, there is a unique r 3 with x r 2 r 3 = 1. We proceed in this fashion until some r j = 0. This must happen since the alternative is that at some point we reach an r k = r j , j + 1 < k .
Since none of the r 's are zero we have u r i - u r i + 1 + px r i r i + 1 ≦ p - 1 or u r i - u r i + 1 ≦ - 1. Summing from i = j to k - 1, we have u r j - u r k = 0 ≦ j + 1 - k , which is a contradiction. Thus all tours include city 0. It remains to observe that no tours is of length greater than p . Suppose such a tour exists, x 0 r 1 , x r 1 r 2 , … , x r p r p +1 = 1 with all r i ≠ 0. Then, as before, u r 1 - u r p +1 ≦ - p or u r p +1 - u r 1 ≧ p .
But we have u r p +1 - u r 1 + px r p +1 r 1 ≦ p - 1 or u r p +1 - u r 1 ≦ p (1 - x r p +1 r 1 ) - 1 ≦ p - 1, which is a contradiction.
Conversely, if the x ij correspond to a legitimate itinerary, it is clear that the u i can be adjusted so that u i = j if city i is the j th city visited in the tour which includes city i , for we then have u i - u j = - 1 if x ij = 1, and always u i - u j ≦ p - 1.
The above integer program involves n ² + n constraints (if t is not fixed) in n ² + 2 n variables. Since the inequality form of constraint is fundamental for integer programming calculations, one may eliminate 2 n variables, say the x i 0 and x 0 j , by means of the equation constraints and produce an equivalent problem with n ² + n inequalities and n ² variables.
The currently known integer programming procedures are sufficiently regular in their behavior to cast doubt on the heuristic value of machine experiments with our model. However, it seems appropriate to report the results of the five machine experiments we have conducted so far. The solution procedure used was the all-integer algorithm of R. E. Gomory [3] without the ranking procedure he describes.
The first three experiments were simple model verification tests on a four-city standard traveling salesman problem with distance matrix [ 20 23 4 30 7 27 25 5 25 3 21 26 ]
The first experiment was with a model, now obsolete, using roughly twice as many constraints and variables as the current model (for this problem, 28 constraints in 21 variables). The machine was halted after 4000 pivot steps had failed to produce a solution.
The second experiment used the earlier model with the x i 0 and x 0 j eliminated, resulting in a 28-constraint, 15-variable problem. Here the machine produced the optimal solution in 41 pivot steps.
The third experiment used the current formulation with the x i 0 and x 0 j eliminated, yielding 13 constraints and 9 variables. The optimal solution was reached in 7 pivot steps.
The fourth and fifth experiments were used on a standard ten-city problem, due to Barachet, solved by Dantzig, Johnson and Fulkerson [1]. The current formulation was used, yielding 91 constraints in 81 variables. The fifth problem differed from the fourth only in that the ordering of the rows was altered to attempt to introduce more favorable pivot choices. In each case the machine was stopped after over 250 pivot steps had failed to produce the solution. In each case the last 100 pivot steps had failed to change the value of the objective function.
It seems hopeful that more efficient integer programming procedures now under development will yield a satisfactory algorithmic solution to the traveling salesman problem, when applied to this model. In any case, the model serves to illustrate how problems of this sort may be succinctly formulated in integer programming terms.
Microalgae are a diverse group of prokaryotic and eukaryotic photosynthetic microorganisms that grow rapidly due to their simple structure. They can potentially be employed for the production of biofuels in an economically effective and environmentally sustainable manner. Microalgae have been investigated for the production of a number of different biofuels including biodiesel, bio-oil, bio-syngas, and bio-hydrogen. The production of these biofuels can be coupled with flue gas CO2 mitigation, wastewater treatment, and the production of high-value chemicals. Microalgal farming can also be carried out with seawater using marine microalgal species as the producers. Developments in microalgal cultivation and downstream processing (e.g., harvesting, drying, and thermochemical processing) are expected to further enhance the cost-effectiveness of the biofuel from microalgae strategy.
Economic Evaluation of CO 2 Storage and Sink Options
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Economic evaluation of CO2 ocean sequestration in Korea National Energy Committee(NEC) The 1st National Energy Master Plan; The 3rd Economic indicators: Chemical Engineering Plant Cost Index (CEPCI): Marshall & swift equipment cost index
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Characteristics of biodegradable plastics (greenpol)
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The economics of CO 2 storage Assess Carbon Dioxide Transportation Options in the Illinois Basin; Midwest Geological Sequestration Con-sortium: 2004
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