A techno-economic case study of CO2 capture, transport and storage chain from a cement plant in Norway

This paper investigates various alternatives for the application of CCS at a cement plant which is one of the focus site for CCS deployment in Norway. A matrix consisting of nine CCS alternative chains is analysed in order to quantify cost reduction potentials across the CCS value chain based on an in-house techno-economic assessment methodology and tool called iCCS. In particular, the paper quantifies the strong cost reduction potential of second generation capture technologies and transport technology selection. CO2 EOR is also identified to have a strong potential to reduce the overall CCS cost, however the cost benefits are strongly dependent on the oil value and the considered EOR injection period. The impact of the inclusion of CO2 capture and conditioning in the cost of cement shows that public financial support will be required to ensure that the plant remain competitive under current cement market price. Finally, comparison of the full-scale capture versus part-scale capture shows, in this case, that the economies of scale are nearly compensated by the additional steam cost, therefore limiting the interest for full-scale implementation. However, joint deployment with the two other CCS potential sites in Norway (Yara and Klemenstrud) may bring more synergie

Techno-economic evaluation of the effects of impurities on conditioning and transport of CO2 by pipeline

This paper describes a detailed technical and economic assessment of conditioning and transporting 13.1 MTPA CO2 with impurities in an on-shore pipe-line over a distance of 500 km. The impurities that are included in the study represents 5 mol% residuals from air-components (N2 and O2) and 10 mol% residuals from natural gas components (N2 and CH4). The analysis includes compression from low pressure, after the captures process, to the pipeline conditions in the dense phase of 150 bar. In the technical analysis of the pipeline transport, thermo-physical properties depending of the pressure and temperature locally as the stream evolves through the pipeline are used as well as heat transferred with the surroundings. The case studies investigate different pipeline diameters from 18″ to 28″ to find the most economical pipeline diameter for each impurity level. The cost model includes the material, labour and energy costs and the result are dependent on the number of required, booster stations, the pipeline wall thickness, the energy consumption and cooling demand. The wall thicknesses are chosen for each investigated diameter based on strength design and rounded off to the next available standard wall thickness according to the API-standard. In the second part, a 24″ pipeline with 4 booster stations is selected and the feed flow rate has been adjusted to match the installed compression power. The results show that for the cost-optimal diameter the specific conditioning and transport cost increases by 13 and 22% for the two cases compared to transporting pure CO2. This represents an increase from 2.3 to 3.8 €/tonCO2. The second scenario, where impure CO2 is transported in an existing pipeline, the cost is shown to be around 20–40% more expensive than transporting pure CO2. The effect on energy consumption and cost from different ambient conditions are also discussed and it is shown that for the selected case the cost of transport will vary 0.01 €/ton/K with change in average temperature from 15 °C as the baseline. Impurities can also be expected to have a significant impact on the technical and economic performances of the whole CCS chain and it is therefore important to evaluate this on a case-to-case bases in order to find possible trade-offs between capture, conditioning, transport and storage and to provide recommendations.submittedVersio

Benchmarking of CO2 transport technologies: Part I—Onshore pipeline and shipping between two onshore areas

This paper focuses on illustrating the CCS chain methodology and the functionality of two transport assessment modules developed within the BIGCCS Research Centre for onshore pipeline and shipping between onshore areas. On the basis of these two modules, technical, costs and climate impact assessments of transport infrastructure and conditioning processes were assessed and compared for a base case. In this case study, onshore pipeline and CO2 shipping between two onshore harbours are compared for different distances and capacities. As expected, for a given annual capacity, onshore pipeline transport should be used for “short” distances, while shipping between harbours is employed for longer distances. Regarding the distance at which the cost-optimal technology switches between the two options, the results show that higher annual capacity and volume would lead to a preference for onshore pipeline transport. The base case can be used as a guide to draw conclusions on particular case studies under the hypotheses presented in this paper. The results also appear to be consistent with the few papers that have compared onshore pipeline and shipping between harbours. Sensitivity analyses were used to address and quantify the impact of several important parameters on the choice of technology. The influences of the individual parameters were then ranked showing that the four most influent parameters on the technology choice are the geographical context, the regional effect of pipeline costs, the First-Of-A-Kind effect, and the ownership effect. Additional work that focuses on transport between a coastal area and an offshore site using either an offshore pipeline or shipping will be presented in Part II of this paper. © 2013 Elsevier Ltd. All rights reserved.acceptedVersio

Toolbox of Effects of CO2 Impurities on CO2 Transport and Storage Systems

There is a need to gather new knowledge on the fundamental properties of CO2 mixtures with impurities and their impact on the chain integrity and economics of Carbon Capture & Storage (CCS) chains. One of the main results from the FP7 IMPACTS project is the IMPACTS toolbox, which comprises new experimental data, thermodynamic reference models for CO2 mixtures relevant for CCS and the framework for CCS risk assessment taking Health Safety & Environment aspects, the impact of the quality of the CO2 and CCS chain integrity into account, and finally the recommendations report.publishedVersio

A Computationally Efficient Formulation of the Governing Equations for Unit Operation Design

A computationally-efficient numerical method that uses a Pseudo-Eulerian formulation (PEF) for the design calculation of unit operations is presented and validated. This method is applicable to any unit operation that can be modelled using a system of ODEs. Performing the design of a unit operation in the PEF is tenfold faster than with the conventional Eulerian formulation (EF). The mathematical equivalence between the PEF and the EF is demonstrated by proving that the solution of different unit operation design problems provides the same numerical result independently of the formulation. It is shown that reducing the computation of the unit operation design problems also speeds the computation time of a process design or an optimization flowsheet. Additionally, as opposed to other computationally efficient methods for unit operation design, the PEF allows the accurate estimation of the concentration or temperature profiles of complex unit operations such as a multiphase multicomponent reactor system

Surrogate modelling of VLE: Integrating machine learning with thermodynamic constraints

An easy-to-implement methodology to develop accurate, fast and thermodynamically consistent surrogate machine learning (ML) models for multicomponent phase equilibria is proposed. The methodology is successfully applied to predict the vapour-liquid equilibrium (VLE) behavior of a mixture containing CO2, monoethanolamine (MEA), and water (H2O). The accuracy of the surrogate model predictions of VLE for this system is found to be satisfactory as the results provide an average absolute relative difference of 0.50% compared to the estimates obtained with a rigorous thermodynamic model (eNRTL + Peng-Robinson). It is further demonstrated that the integration of Gibbs phase rule and physical constraints into the development of the ML models is necessary, as it ensures that the models comply with fundamental thermodynamic relationships. Finally, it is shown that the speed of ML based surrogate models can be ~10 times faster than interpolation methods and ~1000 times faster than rigorous VLE calculations

Multi-criteria Analysis of Two CO2 Transport Technologies

This paper illustrates a methodology for multi-criteria analysis of CCS chains by comparing two transports technologies for a case study in which 10 Mt/y of CO2 from an industrial cluster are transported over 500 km by onshore pipeline and CO2 shipping. This case study compares not only project costs but also other criteria such as the greenhouse gas emissions, the energies and cooling water consumptions etc. The multi-criteria analysis of the two cases shows that the pipeline technology exhibits the best key performance indicators except regarding the initial investment. Indeed the pipeline transport is less expensive, consumes much less utilities (fuel, water and electricity) and is less climate intensive than the shipping transport. The shipping transport required however lower upfront investments for similar overall project costs. A consequence of this might be that even if the pipeline transport has most of the best criteria, shipping might be used during the first CCS chains deployment in order to limit investment upfront, and therefore financial risk, while pipeline transport will be used in a well established CO2 market.publishedVersio

Effect of Uncertainties in Solvent Properties on the Techno-economic Performances of a CO2 Absorber

The use of computational models and simulation tools is vital for design and optimisation of CO2 absorption processes. When developing these tools, mathematical submodels such as models for physical properties and mass and heat transfer models are prerequisite as they are employed to make inferences about the absorption process performance. Although these models are meant to represent and predict the system behavior accurately, they will be compromised due to uncertainties and lack in our knowledge of all the detailes of the physical system. With this motivation, a systematic framework to uncertainty quantification and global sensitivity analysis is presented in this paper in order to account for the uncertainties in solvent properties on a rate-based absorber model (density, viscosity, solubility, surface tension, vapour-liquid equilibrium, chemical reaction and reaction kinetics, heat of reaction, specific heat capacity). In this work, Monte Carlo simulation and Sobol’s indices methodology are applied for the uncertainty quantification. The process chosen for this case study is 30 wt % MEA CO2 capture from the flue gas of a natural gas combined cycle power plant delivering net power output of 830 MWe without capture. The study is based on simultaneously propagating uncertainties in solvent properties and it confirms that the packing height and capital cost of an absorber column might significantly increase in order to achieve a certain CO2 capture ratio with a high level of confidence. Results of the sensitivity analysis also indicate that the reaction rate constant showed the largest impact on the uncertainties in absorber packing height and capital cost followed by viscosity, vapour-liquid equilibrium, density, solubility, heat of absorption, heat capacity and surface tension