Green Twins is our data-driven digital-twin platform aimed to virtually represent, optimize, and eventually control carbon capture in industrial processes, and to minimize the energy cost associated with it. Our project is at the cutting edge of digital applications for carbon capture and shows a potential to be scaled-up. Currently, Innomissions applications have included modelling work as a supporting activity; in Green Twins, models take the center stage and experiments are the support. The goal is to make the digital twin of a pilot plant for solvent-based capture of CO2 from flue gas in Aarhus. The idea is to help inform operators of the plant – and of other carbon capture (industrial) units, in the future – of the details of hidden dynamics of the carbon capture processes in the plant, so that they can optimize CO2 capture and related energy costs.
Our project has originated at DTU (based on our very recent digital-twin article in a Nature’s journal) and will be led by two PIs from DTU Compute, assoc. prof. J. K. Møller and senior researcher G. Goranović. Both are modelling experts and experienced in (co)leading numerous successful Danish and international projects.
Expected impact / output
The Green Twins project contributes to two relevant INNO-CCUS goals. We believe that expected “10% increase in cost efficiency for chemical CO2 capture”, is achievable. Our control algorithm to minimize the energy in the published digital-twin filtration process achieved savings between 50% – 66%.
Job creation in the “… professions such as engineers researching and developing the necessary state-of-art technology”, is difficult to quantify, but there will be new engineering jobs in the niche of green digital twins for CCUS.
Digital twins scale more easily than the physical systems, hence there is opportunity for Denmark to export Green Twins rather than physical counterparts for carbon capture, with global impact. It may be of special interest to address low efficiency and cheap carbon capture systems for developing countries through highly scalable Green Twins.
