Germany is under increasing pressure to rapidly decarbonize its electricity system, while ensuring a secure and affordable electricity supply. In this context, energy storage systems (ESSs) can play a crucial role in enabling a high share of variable renewable electricity generation. To investigate the complex interplay of ESSs in the electricity system, bottom-up energy system optimization models have been utilized to create strategies for the decarbonization of electricity systems at minimum cost. Previous studies have used models to investigate the role of storage technologies in decarbonizing electricity systems. However, in most of them, key aspects pertaining to the optimal storage technology mix (what), the daily and seasonal operation of storage technologies (what), the timing of the investment (when), and their optimal placement (where) are omitted. In this work, we present MANGOelec, a model for the long-term optimal design of electricity systems that allows us to study all the what-where-when dimensions for ESSs. We apply the MANGOelec model to the German electricity system considering the horizon until 2050, as well as various scenarios to investigate the effects of several external factors like building rates of renewable generation technologies or grid expansion limitations on the optimal transformation pathways. The study results indicate that a mix of short- and long-term storage is needed, independent of external factors. For instance, battery storage potentials are close to fully exploited across all regions and the technology is solely used for daily operation. Hydrogen storage, on the other hand, is primarily installed in a small set of regions and operated exclusively as a seasonal storage option. Here, the results indicate that the demand for hydrogen storage capacity is substantial, reaching 2.7–5.9 TWh of hydrogen-based storage capacity in 2050 depending on the scenario. The results also suggest that independent of the storage technology chosen, their deployment commences after 2030 and is completed by 2045. In conclusion, the study shows that already existing ESSs provide sufficient flexibility at first but need to be expanded substantially after 2030 to enable a cost-optimal transition of the German electricity system. Moreover, it illustrates the need for ESSs in order to achieve the decarbonization goals of the German electricity system, which can provide valuable insights to energy planners and policy makers.
Keywords
Energy system scenarios
Electricity system
Energy system modeling
Energy transition
Seasonal storage
Energy storage
