Energy system optimization modelling has become a key ingredient in transitioning to decarbonized energy supply systems based mostly on renewables. Yet, these systems reveal a growing complexity, e.g., due to the decentralization of infrastructures or an increasing variety of potential technologies capable of balancing energy demand and supply. This renders a reliable application of traditional optimization modeling techniques impossible.
In the project UNSEEN, several partners engage in developing model-oriented and algorithmic approaches tailored explicitly for the use of High-Performance Computing (HPC) resources. The prior project BEAM-ME has confirmed the potential of this approach and pointed to further necessities. A core objective in UNSEEN is to profit from methods in AI to speed-up further and facilitate the treatment of large numbers of scenarios in order to cover a larger option space. It will also address the crucial issue of reducing uncertainties when searching for adequate setups of a future energy system in Europe.
Partners are the Zuse Institute Berlin (ZIB), Juelich Supercomputing Center (JSC), GAMS Software GmbH, DLR Institute of Engineering Thermodynamics, DLR Institute of Networked Energy Systems, Institute of Mathematics at TU Berlin.