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.

The adoption of electric vehicles is incentivized by governments around the world to decarbonize the mobility sector. Simultaneously, the continuously increasing amount of renewable energy sources and electric devices such as heat pumps and electric vehicles leads to congested grids. To meet this challenge, several forms of flexibility markets are currently being researched. So far, no analysis has calculated the actual flexibility potential of electric vehicles with different operating strategies, electricity tariffs and charging power levels while taking into account realistic user behavior. Therefore, this paper presents a detailed case study of the flexibility potential of electric vehicles for fixed and dynamic prices, for three charging power levels in consideration of Californian and German user behavior. The model developed uses vehicle and mobility data that is publicly available from field trials in the USA and Germany, cost-optimizes the charging process of the vehicles, and then calculates the flexibility of each electric vehicle for every 15 min. The results show that positive flexibility is mostly available during either the evening or early morning hours. Negative flexibility follows the periodic vehicle availability at home if the user chooses to charge the vehicle as late as possible. Increased charging power levels lead to increased amounts of flexibility. Future research will focus on the integration of stochastic forecasts for vehicle availability and electricity tariffs.

With the increasing penetration of intermittent renewable energy generation, there is a growing demand to use the inherent flexibility within buildings to absorb renewable related disruptions. Heat pumps play a particularly important role, as they account for a high share of electricity consumption in residential units. The most common way of quantifying the flexibility is by considering the response of the building or the household appliances to external penalty signals. However, this approach neither accounts for the use cases of flexibility trading nor considers its impact on the prosumer comfort, when the heat pump should cover the stochastic domestic hot water (DHW) consumption. Therefore, in this paper, a new approach to quantifying the flexibility potential of residential heat pumps is proposed. This methodology enables the prosumers themselves to generate and submit the operating plan of the heat pump to the system operator and trade the alternative operating plans of the heat pump on the flexibility market. In addition, the impact of the flexibility provision on the prosumer comfort is investigated by calculating the warm water temperature drops in the thermal energy storage given heat demand forecast errors. The results show that the approach with constant capacity reservation in the thermal energy storage provides the best solution, with an average of 2.5 min unsatisfactory time per day and a maximum temperature drop of 2.3 °C.

The framework presented provides an open-source, blockchain-based, peer-to-peer energy market platform which can be used for testing different setups or for creating a microgrid peer-to-peer trading platform. The framework offers the following possibilities: · variations of the trading horizon, metering intervals; · simulations within a fraction of the real time; · variations of the number of participants; · multiple operated microgrids within one smart contract; · clearing mechanisms with discriminative prices or a market clearing price; · functionality to log data exchanged with the blockchain; production and consumption data of each participant, electricity exchanged within the microgrid and the main grid, token balances of all participants, · variation of the price ranges.