arXiv subjects

Anton Plietzsch

Publications and source records attributed to Anton Plietzsch.

10 recordsLinked to original sources

arXiv2026

Nodal Braess's Paradox and Inertia Destabilization with Dynamic Node and Line Failures in Power Grids

Large-scale power outages are typically caused by cascading failures. These unfold dynamically through complex interactions between network dynamics and individual component failures. In contrast, the study of cascading failures in physics has focused on analyzing line overloads in the quasi-static regime. We introduce a new model that integrates the dynamics of node and line failures with a paradigmatic oscillator model for power grid synchronization. This enables us to investigate the collective cascading behavior of coupled failures for the first time. We study the impact of nodal robustness, the ability of nodes to tolerate transient disturbances, and inertia, the ability of nodes to resist frequency deviations, on cascade sizes. We discover two novel mechanisms driving system fragility: i) While low inertia is widely considered a major challenge for power grids, we find that high inertia can amplify cascade sizes unless accompanied by appropriate adjustments of other dynamical properties. ii) Further, we find that an increase in the robustness of individual nodes can paradoxically lead to larger cascades. This latter phenomenon constitutes a novel type of Braess's paradox. Understanding such counterintuitive collective effects may become central for achieving resilient future power grids.

nlin.AO↗

arXiv2025

A Port-Hamiltonian Modeling Approach for Integrated Hydrogen Systems

Hydrogen's growing role in the transition towards climate-neutral energy systems necessitates structured modeling frameworks. Existing gas network models, largely developed for natural gas, fail to capture hydrogen systems distinct properties, particularly the coupling of hydrogen pipes with electrolyzers, fuel cells, and electrically driven compressors. In this work, we present a unified systematic port-Hamiltonian (pH) framework for modeling hydrogen systems, which inherently provides a passive input-output map of the overall interconnected system and, thus, a promising foundation for structured analysis, control and optimization of this type of newly emerging energy systems.

math.OC↗

arXiv2024

A Framework for Synthetic Power System Dynamics

The paper is published in Chaos. Please refer to the Chaos version from now on. Anna Büttner, Anton Plietzsch, Mehrnaz Anvari, Frank Hellmann; A framework for synthetic power system dynamics. Chaos 1 August 2023; 33 (8): 083120. https://doi.org/10.1063/5.0155971 Information on power grids is confidential and thus real data is often inaccessible. This necessitates the use of synthetic power grid models in research. So far the models used, for example, in machine learning had to be very simple and homogeneous to produce large ensembles of robust grids. We present a modular framework to generate synthetic power grids that considers the heterogeneity of real power grid dynamics but remains simple and tractable. This enables the generation of large sets of synthetic grids for a wide range of applications. We also include the major drivers of fluctuations on short-time scales. The synthetic grids generated are robust and show good synchronization under all evaluated scenarios, as should be expected for realistic power grids. This opens the door to future research that studies grids under severe stress due to extreme events which could lead to destabilization and black-outs. A software package that includes an efficient Julia implementation of the framework is released as a companion to the paper.

nlin.AO↗

arXiv2023

Protecting the Texas power grid from tropical cyclones: Increasing resilience by protecting critical lines

The Texan electric network in the Gulf Coast of the United States is frequently hit by Tropical Cyclones (TC) causing widespread power outages, a risk that is expected to substantially increase under global warming. Here, we introduce a new approach of combining a probabilistic line fragility model with a network model of the Texas grid to simulate the temporal evolution of wind-induced failures of transmission lines and the resulting cascading power outages from seven major historical hurricanes. The approach allows reproducing observed supply failures. In addition, compared to a static approach, it provides a significant advantage in identifying critical lines whose failure can trigger large supply shortages. We show that protecting only 1% of total lines can reduce the likelihood of the most destructive type of outages by a factor of between 5 and 20. The proposed modelling approach could represent a tool so far missing to effectively strengthen the power grids against future hurricane risks even under limited knowledge.

physics.soc-ph↗

arXiv2022

Linear Response Theory for Renewable Fluctuations in Power Grids with Transmission Losses

We study the spreading of renewable power fluctuations through grids with Ohmic losses on the lines. By formulating a network adapted linear response theory, we find that vulnerability patterns are linked to the left Laplacian eigenvectors of the overdamped eigenmodes. We show that for tree-like networks fluctuations are amplified in the opposite direction of the power flow. This novel mechanism explains vulnerability patterns that were observed in previous numerical simulations of renewable micro-grids. While exact mathematical derivations are only possible for tree like networks with homogeneous response, we show that the mechanisms discovered also explain vulnerability patterns in realistic heterogeneous meshed grids by studying the IEEE RTS-1996 test system.

nlin.AO↗

arXiv2022

A normal form for grid forming power grid actors

Future power grids will be operating a large number of heterogeneous dynamical actors. Many of these will contribute to the fundamental dynamical stability of the system. By taking a complexity theoretic perspective we derive a normal form for grid forming components in power grids. This allows analyzing the grids systemic properties without the need for detailed technical models. Our approach is based on the physics of the power flow in the grid on the one hand, and on the common symmetry that is inherited from the control objectives grid-forming power grid components are trying to achieve. We provide a first experimental validation that this normal form can capture the behavior of complex grid forming inverters without any knowledge of the underlying technology, and show that it can be used to make technology independent statements on the stability of future grids.

nlin.AO↗

arXiv2021

An Open Source Software Stack for Tuning the Dynamical Behavior of Complex Power Systems

BlockSystems.jl and NetworkDynamics.jl are two novel software packages which facilitate highly efficient transient stability simulations of power networks. Users may specify inputs and power system design in a convenient modular and equation-based manner without compromising on speed or model detail. Written in the high-level, high-performance programming language Julia a rich open-source package ecosystem is available, which provides state-of-the-art solvers and machine learning algorithms. Motivated by the recent interest in the Nordic inertia challenge we have implemented the Nordic5 test case and tuned its control parameters by making use of the machine learning and automatic differentiation capabilities of our software stack.

eess.SY↗

arXiv2021

The Risk of Cascading Failures in Electrical Grids Triggered by Extreme Weather Events

One of the serious threats related to climate change is an increase in the number and severity of extreme weather events. A prominent example are hurricanes, which result from rising coastal temperatures. Such extreme weather events can cause extensive damages in infrastructure systems and, potentially, destroy components in electricity transmission networks, which in turn can lead to major blackouts. In our recent work, we study the risk of hurricane-induced cascading failures in power systems of the U.S. East Coast using historical wind field data sets. For this purpose, we model the destruction of overhead transmission lines during hurricanes, where each failing line causes a rerouting of power flow in the system. New power flows can overload additional lines, which are then automatically deactivated and thereby cause another rerouting of power flow and so on. Ultimately, a cascade of failures can unfold that can black out large parts of the power system.

physics.soc-ph↗

arXiv2021

NetworkDynamics.jl -- Composing and simulating complex networks in Julia

NetworkDynamics.jl is an easy-to-use and computationally efficient package for working with heterogeneous dynamical systems on complex networks, written in Julia, a high-level, high-performance, dynamic programming language. By combining state of the art solver algorithms from DifferentialEquations.jl with efficient data structures, NetworkDynamics.jl achieves top performance while supporting advanced features like events, algebraic constraints, time-delays, noise terms and automatic differentiation.

cs.MS↗

arXiv2021

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.

eess.SY↗