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When an author under the pseudonym Satoshi Nakamoto published the paper "Bitcoin: A Peer-to-Peer Electronic Cash System" in 2008, the first cryptocurrency using the new blockchain technology was introduced. Over the last decade, more than 1,000 different cryptocurrencies, such as Ethereum, Ripple, and Litecoin were developed and Bitcoin's currency had almost reached an equivalent value of 20,000 $/BTC. After recognizing the disrupting momentum that the blockchain technology generated, scientists started to develop blockchain use cases for the energy sector. However, the scientific literature so far offers only rough and incomplete estimations when questions about the current and future energy consumption of the Bitcoin network are raised. This paper introduces a new scenario model to estimate the mining power demand of the Bitcoin and Ethereum network. Six scenarios are developed on the basis of mining hardware efficiency and network parameter data. The results show that an increase of the mining hardware efficiency will only have a limited impact on the overall power demand of blockchain networks. Furthermore, the current power demand of the Ethereum network is in the range from 0.6 to 3 GW and therefore, is similar to the one of Bitcoin. In case of linear growth of the block difficulty and sigmoidal increase of the hardware efficiency until the year of 2025, the mining power demand for the Bitcoin blockchain will be approximately 8 GW. Furthermore, the model and the scenarios are adaptable to other cryptocurrencies that use the proof-of-work consensus algorithm to create scenarios for their future power demand.

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The impact of renewable energies on the power grid is continuously increasing. Besides the emission-free power generation, the renewable energies often are the cause for congested grids, component failure and costly interventions by the distribution system operators (DSO) and transmission system operators (TSO) in order to maintain grid stability. The scientific community discusses in recent years the usability of distributed energy resources (DER) as flexible devices. However, no approach can be found that actually quantifies the potential flexibility and sets a price to it. The model presented in this paper optimizes the charging operation of an electric vehicle (EV) according to a price signal with a state of the art exhaustive search algorithm. Furthermore, this model offers all possible deviations from the optimal operation as flexibility to a corresponding market platform and sets a price to each offer, which is dependent on the future price level of the energy. With this model, it is possible to offer positive and negative prices for flexibility. The proposed model shows that an exhaustive enumeration algorithm is feasible to calculate flexibility offers, prices and applicable on currently discussed platform models. The example of an EV charging schedule is successfully modelled and described in this paper.