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Increasing electricity generation from variable renewable energy sources, such as wind and solar, has led to interest in additional short-term and long-term storage capacities. The core objective of this paper is to investigate the costs and the future market prospects of different electricity storage options, such as short-term battery storage and long-term storage as pumped hydro storage, as well as hydrogen and methane from power-togas conversion technologies. The method of approach is based on a formal economic framework with a dynamic component to derive scenarios up to 2040. The major conclusion is that the economic prospects of storage are not very bright. For all market-based storage technologies it will become hard to compete in the wholesale electricity markets and for decentralized (battery) systems it will be hard to compete with the end users' electricity price. The core problem of virtually all categories of storage are low full-load hours (for market-based systems) and low full charge/discharge cycles (for decentralized batteries). However, any new storage capacity should be constructed only in a coordinated way and if there is a clear sign for new excess production, in this case from variable renewables. In addition, for hydrogen and methane there could be better economic prospects in the transport sector due to both, higher energy price levels as well as a general lack of low carbon fuel alternatives.

Battery-powered electric mobility is currently the most promising technology for the decarbonisation of the transport sector, alongside hydrogen-powered vehicles, provided that the electricity used comes 100% from renewable energy sources. To estimate its electricity demand both nationwide and in individual smaller communities, a calculation based assessment on driving profiles that are as realistic as possible is required. The developed model based analysis presented in this paper for the creation of driving and thus electricity load profiles makes it possible to build different compositions of driving profiles. The focus of this paper lies in the analysis of motorised private transport, which makes it possible to assess future charging and load control potentials in a subsequent analysis. We outline the differences in demand and driving profiles for weekdays as well as for Saturdays, Sundays and holidays in general. Furthermore, the modelling considers the length distribution of the individual trips per trip purpose and different start times. The developed method allows to create individual driving and electric vehicle (EV) demand profiles as well as averaged driving profiles, which can then be scaled up and analysed for an entire country.