Das Projekt "Dynamik von Stromnetzen der Zukunft - Selbstorganisation, Stabilität und Optimales Design" wird vom Umweltbundesamt gefördert und von Max-Planck-Gesellschaft zur Förderung der Wissenschaften, Max-Planck-Institut für Dynamik und Selbstorganisation durchgeführt. Distributed, renewable energy sources will dominate the dynamics of future electric power grids. The ongoing change of our energy supply from large, centralized power plants based on nuclear or fossil fuels to smaller, decentralized sources based on renewable energies poses an enormous challenge for design and stable operation of the grid. At the same time, upgrading the grid constitutes a multi-billion Euro business: it is not only it necessary to connect all the new power generators and to enable large-scale energy storage and transport, e.g. from off-shore wind parks to the consumers in the inland. Finally, the structure of the power grid has to be optimized to increase its stability against fluctuations and robustness against failures. A partial future solution will be provided by transmitting consumer infor- mation over the so-called smart grid and adapt energy production and distribution, thus aiming to control the entire grid. However, large-scale failures, for instance, already today are consequences of the collective dynamics of the power grid and are often caused by nonlocal mechanisms. We thus urgently need to understand the intrinsic network dynamics on the large scale to complement partial solutions of control engineering and to be able to develop efficient strategies for operating the future grid. To date, most research on the collective dynamics of power grids follows one of two distinct approaches: Electrical engineers model the behavior of single units of the power grid, such as generators and motors, in great detail and try to approximate the entire grid using a rough proxy structure of only a few units. At the other extreme, physicists and mathematicians mostly studied abstract transportation or flow networks, disregarding all the details of the generators and transmission lines. Bridging the gap between these two approaches, we are now aiming to understand power grid dynamics at an intermediate level using simple but dynamic coarse-scale models. This approach captures the essential features of every element, but is still simple enough to analyze the emergent collective dynamics of the entire power grid and to perform simulations of realistic network structures. Our main objectives are centered around the question how smaller, much more distributed, fluctuating and unreliable power sources impact grid dynamics collectively. Our team in the Network Dynamics Group is studying crucial questions about prediction, failure-control and fault-tolerance as well as non-standard inverse problems such as the optimal design and inference given the relation between grid connectivity and grid dynamics. Results so far: 1) Addition of new transmission lines may *destabilize* power grid operation (via Braess paradox that we identified in oscillator networks). 2) More and smaller but distributed power plants may stabilize grid operation. 3) Coarse-scale modeling of power grids by oscillator networks seems feasible for study of collective, self-or