Dynamic modeling of cost potential curves of captured CO2

Kurzfassung

The field of system modeling and scenario analysis has a demand for high resolution data to drive their models and validate their outputs, in some cases technology related data is not existent or sparse because of novelty or small widespread. This is the case for emission mitigation strategies such as Carbon Capture and Sequestration, which can play a role in emission reduction scenarios. Static CO2 capture potential analysis as well as project-related cost assessments have been thoroughly reported in literature. These approaches have shortcomings. They assume constant boundary conditions and usually focus on a single target year and region. Energy system model analysis however require various geographical scopes and temporal horizons. To address this need, a flexible model is developed to generate cost potential curves in a Geographically distributed manner. In order to test the model, a literature research is done to collect and harmonize input values such as cost and efficiency loss, these are then aggregated and statistically analyzed to create error ranges of the model, given the diversity of the sources the ranges are relatively wide. The geographical distribution is achieved using literature data for industrial processes and open source energy production databases whose missing values are completed using the available information within itself. To fill the gaps mainly in reported efficiency values a computational regression model is built with moderately reliable results of 5% standard error. The cost potential distribution is calculated for the European union and their neighboring countries, examples maps for Germany, Italy and the Netherlands are built from this, insights on the spatial distribution of the sources are done. Curves for Germany are drawn showing a technical potential exceeding 25 Mt/y only from industrial sources wit ha max price of 45 €/t and only on demands of more than 70.7 Mt/y the fossil fuels become relevant with a potential of more than 200 Mt/y with a max price of 110 €/t. Basic scenario developments are modeled for Germany and the EU27 countries using a naive plant closing approach that builds on the GECO scenarios also considering the German coal phase out, the industrial sector development is not modeled. There is a 310 Mt/y potential difference between the Reference and 1.5°C scenarios for the EU27 countries and no difference for Germany as the scenario emission goals are met by German coal phase-out by 2038. A sensitivity analysis shows that higher efficiency losses imply a lower marginal cost of CO2, the same can be said for the Capacity factor effect, reducing the capture efficiency from 90 % to 50% increases the cost from 80 €/t to 150 €/t and the potential is reduced from 1500Mt/y to 750 Mt/y . To further validate the data, cross-validation of the amounts is done using Emission Reports compiled in the PRIMAP project but the comparison potential is limited given the high dependency of assumptions. Similarly with the aid of an alternative data source it was found that the whole structure of the curve is sensitive to the input by changing the max potential from 1800 Mt/y to 1600 Mt/y and the median cost from 75 €/t to 50 €/t. With the available data it is concluded that the production does not represent a bottleneck in the CO2 supply chain.