Energy system optimization modeling 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.