This paper presents a framework for estimating the future N^th-of-a-kind (NOAK) cost of advanced low-carbon technologies that are currently at early pre-commercial stages of development. It identifies two types of question that commonly motivate a cost analysis: “What If” questions about the hypothetical future cost of a technology that meets specified R&D goals or requirements; and “What Will” questions regarding the true expected cost of an advanced technology once it is mature and widely deployed. The latter type of question is the focus of this paper. It addresses shortcomings in the “bottom up” engineering-economic method current used to estimate NOAK costs. It describes a more rigorous hybrid costing method that combines a bottom-up analysis of the first-of-a-kind (FOAK) commercial cost of an advanced technology with an empirical model employing experience curves to project its future cost. Guidelines are presented for all phases of the analysis.

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Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 capture and storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are novel concepts, that are still in the early (pre-commercial) stages of development. Therefore, uncertainties in their technology performance and cost are often substantial, making it imperative that they be characterized, and their impacts reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. There are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and cost studies.@en

After a 13,000-hour test campaign with aqueous 30 wt% MEA (2-aminoethanol) solvent at the CO₂ capture pilot plant at Niederaussem, another long-term test was carried out as part of the ALIGN-CCUS project. This test ran for more than 12,275 hours with aqueous AMP/PZ (2-Amino-2-methyl-1-propanol/piperazine) solvent, named CESAR1 (3.0 molar AMP (~26.74 wt%) and 1.5 molar PZ (~12.92 wt. %)). A minimum specific reboiler duty of 2,970 MJ/t_CO2 was identified for the capture plant operation with four active absorber beds (total 16 m packing height) and intercooling (40°C). Neither a lower desorber pressure of 1.5 bar(a), instead of 1.75 bar(a), nor a change of the different positions of intercooling had a significant effect on energy consumption. Reduction of the active packing height to three beds (i.e., 12 m), resulted in a moderately higher specific energy demand (+100 MJ/t_CO2). Tests with CO₂ capture rates between 90 and 98% showed only a small increase of the specific energy demand at 95% (+20 MJ/t_CO2) and four active packings (98%: +250 MJ/t_CO2). The average solvent consumption of CESAR1 during 400 days of operation was 0.45 kg/t_CO2 and is lower than for MEA if the phase of accelerated non-linear degradation of MEA is taken into account. CESAR1 follows a slow-progressing linear degradation behavior; neither a critical metal ion concentration threshold value could be found that triggers fast degradation nor a correlation between accumulated trace components or metal ion concentrations in the solvent and the degradation rate was observed. Highly transient tests were conducted to investigate the dynamic behavior of the capture plant and subsequently special settings were chosen to stimulate high emissions for the investigation of aerosol-based emissions, connected with performance tests of several emission mitigation measures: single water wash, double water wash, acid wash, dry bed, wet electric precipitator and flue gas pre-treatment. When applying the dry bed configuration, emissions of AMP between 15 - 20 mg/Nm³, PZ between 3 - 7 mg/Nm³, and NH₃ below 3 mg/Nm³ were achieved.

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Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO₂ Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.

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This work compares the part load techno-economic performance of CO₂ capture from a combined cycle gas turbine (CCGT) using a membrane configuration with selective CO₂ recycle and using monoethanolamine (MEA) solvent, under the assumption of flexible power plant dispatch. This is the first time that the techno-economic performance of CO₂ capture technologies is compared assuming a flexible dispatch profile, and the assessment was done using a comprehensive, new, part load assessment approach. Analyzing the part load performance of CO₂ capture and storage (CCS) technologies is relevant because of significant changes in our power systems, dramatically reducing the utilization of thermal power plants. The technical performance of the configurations with and without CCS was simulated at steady state, at operating points between maximum continuous rating (100% gas turbine loading) and minimum stable load (35% gas turbine loading). The performance at these operating points was then aggregated into weighted averages to produce single performance indicators (specific CO₂ intensity, specific primary energy per tonne of CO₂ avoided (SPECCA), and levelized cost of electricity (LCOE)) over the dispatch profile of the power plant. The technical performance of the MEA configuration was favorable over the membrane configuration over the whole CCGT loading range. The MEA SPECCA increased from 3.02 GJ/(t of CO₂) at 100% GT loading to 3.65 GJ/(t of CO₂) at 35% GT loading; the membrane SPECCA increased from 3.35 to 4.20 GJ/(t of CO₂). The higher SPECCA of the membrane configuration is caused by the reduced gas turbine efficiency, due to the selective recycling of CO₂ to the GT. When equal GT efficiency was assumed for combustion with normal air and with CO₂ enriched air, the membranes' technical performance was comparable with that of MEA. The capital costs of the CCGT with membrane configuration were 35% higher than the CCGT with MEA configuration. That, and the 6 year replacement frequency of the membranes, led the membrane LCOE to be 10 €/(MW h) higher than the MEA LCOE, when calculated with the part load approach. The membrane LCOE was 8 €/(MW h) higher when a full load was assumed. The new part load approach proved instrumental in highlighting performance (differences) at flexible dispatch conditions and aggregating those into easy to understand performance indicators.

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This work describes an analysis of the techno-economic performance of CCGT’s with an advanced membrane concept and compares this with MEA postcombustion capture. The analysis is undertaken at part-load (off-design) conditions to mimic realistic power plant dispatch. It integrates the part-load performance of operating points from minimal stable load to maximum continuous rating into weighted single techno-economic performance indicators that allow comparing the performance of CCS technologies under more realistic conditions than full load.@en

An approach for the techno-economic assessment of power plants with and without carbon capture and storage (CCS) is proposed. A state-of-the-art natural gas combined cycle (NGCC) power plant is selected equipped with post-combustion CO₂ capture technology (MEA). The technoeconomic indicators are calculated using both the conventional and part load approaches. The economic results also show significant differences between the full load and the part load approaches. The results show that the levelized cost of electricity (LCOE) of gas-based power generation with CCS will more likely be above 100 €/MWh than below this value. This inherently also leads to an increase of the cost of CO₂ avoided in the order of 20-100%. The observed differences between the full load and part load approaches showcase the necessity for including real dispatch profiles when calculating the technoeconomic performance of CCS power.

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This paper addresses the uncertainty and variability in techno-economic studies of carbon capture technologies, based on a detailed comparison of the results of different studies on postcombustion CO2 capture with advanced amines, and on an in-depth uncertainty analysis using a combination of sensitivity and pedigree analyses. The results show that despite efforts to harmonize capital cost estimates, the capital cost results of the same PCC carbon capture systems can still show large (65%) differences. This uncertainty may simply be inherent to early stage cost estimates. Amongst the most important causes for the variability shown in this work are differences in equipment sizing methods and purchased equipment cost estimates. This capital cost variability only mildly propagates into the Levelised Cost of Electricity and Cost of CO2 Avoided, more so in case of low power plant utilisation scenarios. To enhance insight into these uncertainties and enable their communication, the paper argues to use in-depth uncertainty evaluation for early stage techno-economic studies. It suggests to complement current practice of sensitivity analysis with pedigree analysis and to combine the results of both analyses in diagnostic diagrams. This may lead to more informed interpretation of the results of techno-economic studies, and helps focus techno-economic research efforts towards the parameters that most influence final performance indicators.@en

This work presents the results of a comparative life cycle assessment study for three CCS technologies applied to a coal-fired power plant: post-combustion capture with MEA, post combustion capture with AMP/PZ and cryogenic oxy-fuel. This study has been performed in the context of the EDDiCCUT project, which aims to develop an environmental due diligence framework for assessing novel CCUS technologies. The research shows that there are no significant differences in climate change potential (CCP) for the technologies under study. In the three cases the reduction is about 70% (70% for the plant with MEA, 71% for the plant with AMP-PZ, and 73% for the plant with oxy-fuel technology). With regard to other impacts (e.g., acidification, toxicity, resource depletion) the results show an increase in the impacts as consequence of CCS, mostly driven by the increase amount of feedstock per kWh. Contrary to CCS, there are clear differences among the technologies with results ranging between 20 and 30%. Toxicity impacts related to the operation of the solvent-based carbon capture unit were also considered; however, it was observed that their contribution was only around 2% of the total impact for human toxicity potential. Rather, the largest contributor to human toxicity impacts in the life cycle of coal power plants with and without CCS is coal mining waste disposal.

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CO₂ utilisation is gaining interest as a potential element towards a sustainable economy. CO₂ can be used as feedstock in the synthesis of fuels, chemicals and polymers. This study presents a prospective assessment of carbon capture from a hydrogen unit at a refinery, where the CO₂ is either stored, or partly stored and partly utilised for polyols production. A methodology integrating technical, economic and environmental models with uncertainty analysis is used to assess the performance of carbon capture and storage or utilisation at the refinery. Results show that only 10% of the CO₂ captured from an industrial hydrogen unit can be utilised in a commercial-scale polyol plant. This option has limited potential for large scale CO₂ mitigation from industrial sources. However, CO₂ capture from a hydrogen unit and its utilisation for the synthesis of polyols provides an interesting alternative from an economic perspective. The costs of CO₂-based polyol are estimated at 1200 €/t polyol, 16% lower than those of conventional polyol. Furthermore, the costs of storing the remaining CO₂ are offset by the benefits of cheaper polyol production. Therefore, the combination of CO₂ capture and partial utilisation provides an improved business case over capture and storage alone. The environmental assessment shows that the climate change potential of this CO₂ utilisation system is 23% lower compared to a reference case in which no CO₂ is captured at the refinery. Five other environmental impact categories included in this study present slightly better performance for the utilisation case than for the reference case.

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CO 2 utilization is increasingly considered a greenhouse gas abatement strategy alternatively to CO 2 storage. Existing indicators that assess the performance of CO 2 utilization options often provide an incomplete perspective and are unsuitable to compare different utilization options with different functionality (e.g. plastics and fuels). This study introduces a new performance indicator for CO 2 utilization options: Specific Primary Energy Consumption per unit of Fossil feedstock Replaced (SPECFER). This indicator, expressed in MJ/MJ, provides a proxy for the energy efficiency of which CO 2 conversion options can replace fossil feedstock required in conventional processes. Three CO 2 utilization case studies (CO 2 based methanol, polyols and dimethyl ether) are used to show the application and effectiveness of the SPECFER indicator. Among the case studies, only CO 2 conversion into polyol appears particularly efficient (SPECFER of 0.05 MJ/MJ), while the other options are not (SPECFER of > 1 MJ/MJ). The paper shows that the SPECFER indicator adds key insights compared to conventi onal indicators to the effectiveness of CO 2 utilization options and is a promising indicator complementary to CO 2 emissions reduction or life cycle greenhouse gas reduction potential. The SPECFER thus improves the understanding of the performance of CO 2 utilization and enables the possibility to distinctly compare different CO 2 converting utilization technologies.@en

this work addresses the methodological challenges of undertaking techno-economic assessments of very early stage (technology readiness level 3–4) CO₂ capture technologies. It draws lessons from a case study on CO₂ capture from a natural gas combined cycle with exhaust gas recycle and electric swing adsorption technology. The paper shows that also for very early stage technologies it is possible to conduct techno-economic studies that give a sound first indication of feasibility, providing certain conditions are met. These conditions include the availability of initial estimates for the energy use of the capture technology, either from bench scale measurements, or from rigorous process models, and the possibility to draw up a generic (high level) equipment list. The paper shows that for meaningful comparison with incumbent technologies, the performance of very early stage technologies needs to be projected to a future, commercial state. To this end, the state of the art methods have to be adapted to control for the development and improvements that these technologies will undergo during the R&D cycle. We call this a hybrid approach. The paper also shows that CO₂ capture technologies always need to be assessed in sympathy with the CO₂ source (e.g. power plant) and compression plant, because otherwise unreliable conclusions could be drawn on their feasibility. For the case study, it is concluded that electric swing adsorption is unlikely to become economically competitive with current technologies, even in a highly optimised future state, where 50% of the regeneration duty is provided by LP steam and 50% by electricity: the net efficiency of an NGCC with EGR and optimised ESA (49.3%_LHV; min–max 45.8–50.4%_LHV) is lower than that of an NGCC with EGR and standard MEA (50.4%_LHV). Also, investment and operational costs are higher than MEA, which together with ESA's lower efficiency leads to an unfavourable levelised cost of electricity: 103 €/MWh (min–max 93.89–117.31 €/MWh) for NGCC with ESA, versus 91 €/MWh for NGCC with MEA.

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This work presents a techno-economic analysis of a 2015 state-of-the art ASC PC oxyfuel power plant. This work adds to the existing body of techno-economic studies on coal oxycombustion that use less advanced oxyfuel technology and/or steam cycles. The study shows that this oxyfuel configuration has a net efficiency about 2%-pt. higher than a similar ASC PC plant with MEA postcombustion technology. This is partly due to the high gross efficiency of the oxyfuel power plant. The capital costs, LCOE, and cost of CO₂ avoided of the oxyfuel configuration are, however, slightly higher than those of the MEA configuration, despite the high efficiency of the oxyfuel plant. This means that the good technical performance of this state of the art oxy-fired coal plant is not necessarily translated into equally favourable economic performance. Rather, oxyfuel and PCC performance are rather comparable.

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We studied the possibility of converting waste toilet paper (WTP) into electricity. WTP is a waste stream with continuous availability and negative cost, but it is difficult to handle, as it contains fecal matter. The process we explored had two stages: WTP gasification followed by direct conversion into electricity in a high-temperature solid-oxide fuel cell (SOFC). The process was studied on a 10 ktpa scale by using real-life parameter values obtained from industrial sources. We presented the basic system design, as well as its electricity yield and overall efficiency on the basis of detailed mass- and energy-balance calculations. By explorative technoeconomic analysis and sensitivity analysis, we found an electric efficiency of 57 %, which is similar to that of a natural gas combined cycle plant. The levelized cost of electricity (LCOE) was 20.3 ¢ kWh⁻¹, which is comparable at present to that of residential photovoltaic installations. The system's capital costs are relatively high, mainly as a result of SOFC investment costs, but we expect these costs to decrease as the market of cells develops. The operating costs are relatively low, partly thanks to the high thermodynamic efficiency (≈70 %). Currently, the fuel costs are negative (because we use waste as a raw material), yet this could change if the value of WTP would increase as a result of this process. Learning effects could make the system more competitive in the future with an LCOE of approximately 11 ¢ kWh⁻¹.

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This study presents the development, application, and uncertainty analysis of a process simulation model for postcombustion CO₂ capture with an AMP/PZ solvent blend based on state of the art knowledge on AMP/PZ solvent technology. The development includes the improvement of the physical property models of a software package designed for simulation of acid gas treatment and CO₂ capture technologies. The improvement particularly consisted of regression of AMP-PZ binary interaction parameters. The model was applied to a case study of postcombustion CO₂ capture from an Advanced Super Critical Pulverized Coal power plant. Uncertainly analysis was undertaken by validating the physical property models against laboratory measurements reported in literature; by comparing model results with pilot study results, and by evaluating the strength of the model with a novel method called pedigree analysis. The results show that AMP/PZ postcombustion technology performs better than MEA technology on most performance indicators, e.g., the Specific Reboiler Duty is reduced from 3.6 GJ/t CO₂ for MEA, to 2.9 GJ/t CO₂ for AMP/PZ, and the specific cooling water requirement is reduced from 4.1 to 3.4 GJ/t CO₂. Only amine slip to the atmosphere increases with AMP/PZ technology: from 0.18 g/t CO₂ to 15.3 g/t CO₂, although this value is still within emission limits from existing regulatory frameworks. The coal power plant net efficiency with AMP/PZ capture amounts to a value of 37.2%_LHV, compared to 46.1%_LHV for the case without CCS and 36.2%_LHV in case of CCS with MEA. The uncertainty analysis shows that the model is well capable of predicting experimental and pilot result. The remaining uncertainty is mostly in the reaction kinetics and in the flowsheet design. Validation could be further improved, by more elaborate comparison to independent measures of physical properties, and by comparison of the model outputs to results from large demonstration or commercial size capture plants.

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This article aims to improve uncertainty evaluation of process models by combining a quantitative uncertainty evaluation method (data validation) with a qualitative uncertainty evaluation method (pedigree analysis). The approach is tested on a case study of monoethanolamine based postcombustion CO₂ capture from a coal power plant. Data validation was used to quantitatively assess the uncertainty of the inputs and outputs of the MEA model. Pedigree analysis was used to qualitatively assess the uncertainty in the current knowledge base on MEA carbon capture systems, the uncertainty in the MEA process model, and the uncertainty of the MEA model results. The pedigree review was done by 13 international experts in the field of postcombustion carbon capture with chemical solvents. The data validation showed that our MEA model is accurate in predicting specific reboiler duty, and CO₂ stream purity (4% and 1% difference respectively between model and pilot plant results), but in first instance it was less accurate in predicting liquid over gas ratio, and cooling water requirement (54% and 23% difference respectively between model and pilot plant results). The pedigree analysis complemented these results by showing that there was fairly high uncertainty in the thermodynamic, and chemistry submodels, as reflected in the low pedigree scores on most indicators. Therefore, the model was improved to better resemble pilot plant results. The results indicate that using a pedigree approach improved uncertainty evaluation in three ways. First, by highlighting sources of uncertainty that quantitative uncertainty analysis does not take into account, such as uncertainty in the knowledge base regarding a specific phenomenon. Second, by providing a systematic approach to uncertainty evaluation, thereby increasing the awareness of modeller and model user. And finally, by presenting the outcomes in easy to understand numerical scores and colours, improving the communication of model uncertainty. In combination with quantitative validation efforts, the pedigree approach can provide a strong method to gain deep insight into the strengths and weaknesses of a process model, and to communicate this to policy and decision-makers.

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Carbon capture and storage is considered a promising option to mitigate CO2 emissions. This has resulted in many R&D efforts focusing at developing viable carbon capture technologies. During carbon capture technology development, process modeling plays an important role. Selecting an appropriate process model for carbon capture technologies is not trivial, because of the large range of technology options, the difference in technology development stage, and the different purposes for which a process model can be used. This paper proposes a five-step, structured approach, designed to support the selection of carbon capture process models. The approach is illustrated with a post-combustion (monoethanolamine) case study. The paper shows intermediate and output results of the structured approach, and of the MEA case.@en