Electricity transmission expansion has suffered many delays in Europe in recent decades, despite its importance for integrating renewable electricity into the energy system. A hydrogen network which reuses the existing fossil gas network would not only help supply demand for low-emission fuels, but could also help to balance variations in wind and solar energy across the continent and thus avoid power grid expansion. We pursue this idea by varying the allowed expansion of electricity and hydrogen grids in net-zero CO2 scenarios for a sector-coupled European energy system with high shares of renewables and self-sufficient supply.

Using corrective actions to overcome network loading when single lines fail has the potential to free up network capacity that is otherwise underused in preventive N-1 security strategies. We investigate the impact on renewable integration of a corrective network security strategy, whereby storage or other flexibility assets are used to correct overloading that results from line outages. In a 50-bus model of the German power system utilizing these flexibility assets, so-called network boosters (NB), we find significant cost savings for the integration of renewable energy of up to 0.

To achieve ambitious greenhouse gas emission reduction targets in time, the planning of future energy systems needs to accommodate societal preferences, e.g.~low levels of acceptance for transmission expansion or onshore wind turbines, and must also acknowledge the inherent uncertainties of technology cost projections. To date, however, many capacity expansion models lean heavily towards only minimising system cost and only studying few cost projections. Here, we address both criticisms in unison. While taking account of technology cost uncertainties, we apply methods from multi-objective optimisation to explore trade-offs in a fully renewable European electricity system between increasing system cost and extremising the use of individual technologies for generating, storing and transmitting electricity to build robust insights about what actions are viable within given cost ranges.