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This paper reports the key findings and conclusions of a study that analyzes the financing of large-scale CO 2 Capture and Storage (CCS) demonstration projects worldwide. By looking across dozens of CCS demonstration projects that have been under development, both completed and cancelled, one can identify the ingredients necessary for success, as well as pitfalls to avoid. This paper summarizes how “successful” CCS demonstration projects were financed, reviews the largest government programs designed to help finance these projects, and reports on the lessons learned. [ABSTRACT FROM AUTHOR]

In this paper, techno-economic analysis of direct coal biomass to liquids (CBTL) plants is performed in Aspen Process Economic Analyzer (APEA) using high fidelity process models developed in Aspen Plus for four different configurations of direct CBTL plants. Results from the economic model are validated with the data in the open literature, if available. Sensitivity studies are conducted to evaluate the impacts of key investment parameters, design parameters, and potential government-subsidized credits on the main economic measures including net present value (NPV), internal rate of return (IRR), break-even oil price (BEOP) and equivalent oil price (EOP). Using the North America 2015 pricing basis in APEA, this study shows that the BEOP of direct CBTL processes ranges from $56.9/bbl to $80.5/bbl for large scale (50,000 bbl/day) plants and from $77.3/bbl to $97.5/bbl for small scale (10,000 bbl/day) plants. It is observed that integrating a carbon capture and storage (CCS) unit to the direct CBTL process can increase the BEOP by about 10%, while utilization of the cheap and abundant shale gas (especially in the continental US) can make the direct liquefaction processes considerably more attractive than the indirect CBTL processes. [ABSTRACT FROM AUTHOR]

India's developmental needs in the near and long-term future will be strongly interlinked with the need to provide steady electricity to its cities and villages. The current fleet of Electricity Generating Units (EGUs) in India is mostly coal-based. These coal-fired power plants lead to a substantial amount of CO 2 emissions. Due to international climate obligations, there might be a need to limit the amount of unmitigated CO 2 emissions being emitted into the atmosphere. Mitigation of such emissions at coal-fired power plants offers an easily controllable way of reducing such emissions. The mechanisms to reduce emissions in coal-fired power plants may be through installation of super-critical units, repowering the plant with Integrated Gasification Combined Cycle (IGCC) or with use of coal blended with biomass. More radical emission cuts may be obtained by retrofitting the existing plants with CO 2 Capture and Storage (CCS), a technology with the ability to reduce the emissions by 80-85% of the current emissions levels. This paper begins with a brief insight into some of the mechanisms to cause emission reductions in coal-fired power plants. It focuses mainly of how retrofitting the power plants with CCS technology will affect the techno-economic of the plant. Three types of plants will be analyzed, viz, Low performance, medium performance and high performance; the categorization being based on the current Indian fleet of EGUs. We analyze five pathways for mitigation, with two focusing on efficiency improvements and three on CCS technology. The results show that overall cost of avoidance for CCS ranges from US$ 59.54 to US$ 85.41 per tonne of CO 2 . There is a strong incentive for repowering of old plants to supercritical units and their subsequent retrofitting with CO 2 capture systems than direct retrofitting of low performance plants. [ABSTRACT FROM AUTHOR]

This paper presents a thorough thermodynamic analysis and optimization of the NET Power cycle (also called Allam cycle), a natural-gas-fired oxy-combustion cycle featuring nearly 100% CO 2 capture level, very high net electric efficiency, and potentially near-zero emissions level. The main goals of this study are the systematic optimization of the cycle for the maximum efficiency, and the quantification of the effects of the modelling assumptions and equipment performance on the optimal cycle variables and efficiency. An Aspen Plus flow-sheet featuring accurate first-principle models of the main equipment units (including cooled turbine) and fluid properties (equation of state) has been developed. The influence of the cycle variables on the thermodynamic performance of the cycle is first assessed by means of sensitivity analyses. Then, the cycle variables, which maximize the net electric efficiency, are determined with PGS-COM, a black-box numerical optimization algorithm, linked to the simulation software. The corresponding maximum cycle efficiency is equal to 54.80% (with 100% CO 2 capture), confirming the outstanding performance of the NET Power cycle. Moreover, the optimization indicates the existence of promising combinations of the cycle variables which lead to reduced component costs (due to the lower operating pressures and temperatures) of the most critical components, without considerably affecting the net electric efficiency. The analysis also indicates that the cooling medium temperature, the power consumption of the air separation unit, the effectiveness of the regenerator and the effectiveness of the turbine cooling system are the main factors influencing the cycle efficiency. [ABSTRACT FROM AUTHOR]

The paper analyses the impact that European Union citizens’ access to information on climate change has on their awareness of carbon capture and storage (CCS), perceived risks and benefits of using CCS and stated choice of preferred CCS options. We use a Eurobarometer dataset about awareness/acceptance of CCS and run structural equation models (SEM) for twelve EU countries with an average sample size of 1,100 observations per country. Results between the different countries are comparable and, alongside other determinants, access to information sources will significantly impact CCS awareness, perceived risk and benefits of CCS and preferences towards options of CCS. [ABSTRACT FROM AUTHOR]