Bounds and Estimates for the Response to Correlated Fluctuations in Asymmetric Complex Networks

We study the spreading of correlated fluctuations through networks with asymmetric and weighted coupling. This can be found in many real systems such as renewable power grids. These systems have so far only been studied numerically. By formulating a network adapted linear response theory, we derive an analytic bound for the response. For colored we find that vulnerability patterns noise are linked to the left Laplacian eigenvectors of the overdamped modes. We show for a broad class of tree-like flow networks, that fluctuations are enhanced in the opposite direction of the flow. This novel mechanism explains vulnerability patterns that were observed in realistic simulations of renewable power grids

Can Distribution Grids Significantly Contribute to Transmission Grids' Voltage Management?

Power generation in Germany is currently transitioning from a system based on large, central, thermal power plants to one that heavily relies on small, decentral, mostly renewable power generators. This development poses the question how transmission grids' reactive power demand for voltage management, covered by central power plants today, can be supplied in the future. In this work, we estimate the future technical potential of such an approach for the whole of Germany. For a 100% renewable electricity scenario we set the possible reactive power supply in comparison with the reactive power requirements that are needed to realize the simulated future transmission grid power flows. Since an exact calculation of distribution grids' reactive power potential is difficult due to the unavailability of detailed grid models on such scale, we optimistically estimate the potential by assuming a scaled, averaged distribution grid model connected to each of the transmission grid nodes. We find that for all except a few transmission grid nodes, the required reactive power can be fully supplied from the modeled distribution grids. This implies that - even if our estimate is overly optimistic - distributed reactive power provisioning will be a technical solution for many future reactive power challenges

The impact of model detail on power grid resilience measures

Peer reviewedPreprin

Taming Instabilities in Power Grid Networks by Decentralized Control

Renewables will soon dominate energy production in our electric power system. And yet, how to integrate renewable energy into the grid and the market is still a subject of major debate. Decentral Smart Grid Control (DSGC) was recently proposed as a robust and decentralized approach to balance supply and demand and to guarantee a grid operation that is both economically and dynamically feasible. Here, we analyze the impact of network topology by assessing the stability of essential network motifs using both linear stability analysis and basin volume for delay systems. Our results indicate that if frequency measurements are averaged over sufficiently large time intervals, DSGC enhances the stability of extended power grid systems. We further investigate whether DSGC supports centralized and/or decentralized power production and find it to be applicable to both. However, our results on cycle-like systems suggest that DSGC favors systems with decentralized production. Here, lower line capacities and lower averaging times are required compared to those with centralized production.Comment: 21 pages, 6 figures This is a pre-print of a manuscript submitted to The European Physical Journal. The final publication is available at Springer via http://dx.doi.org/10.1140/epjst/e2015-50136-

Stability of Synchrony against Local Intermittent Fluctuations in Tree-like Power Grids

ACKNOWLEDGMENTS S.A. wants to thank her fellow colleagues Paul Schultz and Jobst Heitzig for helpful discussion and comments. The authors gratefully acknowledge the support of BMBF, CoNDyNet, FK. 03SF0472A and the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources on the high performance computer system at the Potsdam Institute for Climate Impact Research.Peer reviewedPublisher PD

Collaborative Work on Ontologies - A Report

Supply chains are vulnerable and inherently complex processes. In-creasing the resilience of supply chains is realised, if the stakeholders involved have agreed on a clear language. Only this enables a comprehensive, unambiguous and fast exchange of information. Ontologies serve as a powerful formal tool to realize an appropriate communication framework. They are designed to make communication and information exchange between stakeholders and machines unambiguous and thus efficient. This paper addresses the challenges and solutions associated with the fact that ontologies need to reflect agreed definitions of a domain, as we face them in the SC3 and CoyPu projects

PowerDynamics.jl—An experimentally validated open-source package for the dynamical analysis of power grids

PowerDynamics.jl is a Julia package for time-domain modeling of power grids that is specifically designed for the stability analysis of systems with high shares of renewable energies. It makes use of Julia’s state-of-the-art differential equation solvers and is highly performant even for systems with a large number of components. Further, it is compatible with Julia’s machine learning libraries and allows for the utilization of these methods for dynamical optimization and parameter fitting. The package comes with a number of predefined models for synchronous machines, transmission lines and inverter systems. However, the strict open-source approach and a macro-based user-interface also allows for an easy implementation of custom-built models which makes it especially interesting for the design and testing of new control strategies for distributed generation units. This paper presents how the modeling concept, implemented component models and fault scenarios have been experimentally tested against measurements in the microgrid lab of TECNALIA.This research has been performed using the ERIGrid Research Infrastructure and is part of a project that has received funding from the European Union’s Horizon 2020 Research and Innova-tion Programme under the Grant Agreement No. 654113. The support of the European Research Infrastructure ERIGrid and its partner TECNALIA is very much appreciated. We further acknowl-edge the Support by BMBF(CoNDyNet2FK.03EK3055A), the DFG (ExSyCo-Grid, 410409736), the Leibniz competition (T42/2018) and the Federal Ministry of Economics (MAriE, FK. 03Ei4012B)