The integration of rising shares of volatile wind power in the generation mix is a major challenge for the future energy system. To address the uncertainties involved in wind power generation, models analysing and simulating the stochastic nature of this energy source are becoming increasingly important. One statistical approach that has been frequently used in the literature is the Markov chain approach. Recently, the method was identified as being of limited use for generating wind time series with time steps shorter than 15-40 min as it is not capable of reproducing the autocorrelation characteristics accurately. This paper presents a new Markov-chain-related statistical approach that is capable of solving this problem by introducing a variable second lag. Furthermore, additional features are presented that allow for the further adjustment of the generated synthetic time series. The influences of the model parameter settings are examined by meaningful parameter variations. The suitability of the approach is demonstrated by an application analysis with the example of the wind feed-in in Germany. It shows that-in contrast to conventional Markov chain approaches-the generated synthetic time series do not systematically underestimate the required storage capacity to balance wind power fluctuation.

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Due to the increasing share of renewable energy sources in the electrical network, the focus on decarbonization has extended into other energy sectors. The gas sector is of special interest because it can offer seasonal storage capacity and additional flexibility to the electricity sector. In this paper, we present a new simulation method designed for hydrogen-enriched natural gas network simulation. It can handle different gas compositions and is thus able to accurately analyze the impact of hydrogen injections into natural gas pipelines. After describing the newly defined simulation method, we demonstrate how the simulation tool can be used to analyze a hydrogen-enriched gas pipeline network. An exemplary co-simulation of coupled power and gas networks shows that hydrogen injections are severely constrained by the gas pipeline network, highlighting the importance and necessity of considering different gas compositions in the simulation.

The ongoing energy transition requires power grid extensions to connect renewable generators to consumers and to transfer power among distant areas. The process of grid extension requires a large investment of resources and is supposed to make grid operation more robust. Yet, counter-intuitively, increasing the capacity of existing lines or adding new lines may also reduce the overall system performance and even promote blackouts due to Braess’ paradox. Braess’ paradox was theoretically modeled but not yet proven in realistically scaled power grids. Here, we present an experimental setup demonstrating Braess’ paradox in an AC power grid and show how it constrains ongoing large-scale grid extension projects. We present a topological theory that reveals the key mechanism and predicts Braessian grid extensions from the network structure. These results offer a theoretical method to understand and practical guidelines in support of preventing unsuitable infrastructures and the systemic planning of grid extensions.

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