Abstract
To analyse the relationship between stability against large perturbations and topological properties of a power transmission grid, we employ a statistical analysis of a large ensemble of synthetic power grids, looking for significant statistical relationships between the single-node basin stability measure and classical as well as tailormade weighted network characteristics. This method enables us to predict poor values of single-node basin stability for a large extent of the nodes, offering a node-wise stability estimation at low computational cost. Further, we analyse the particular function of certain network motifs to promote or degrade the stability of the system. Here we uncover the impact of so-called detour motifs on the appearance of nodes with a poor stability score and discuss the implications for power grid design.
Highlights
We propose a strategy to directly estimate the power grids stability, even on short time scales, using statistical network characteristics to omit the need of costly simulations
We investigate the question if—in contrast to destabilising dead trees— there are network motifs promoting the dynamical stability of a power grid
The two main results of our analysis are the identification of the detour motif being important for enhancing power grid stability and a statistical model to predict poor singlenode basin stability using only a small set of standard and novel network characteristics as explanatory variables
Summary
Following a sequence of large-scale blackout events [2, 17, 21] within the last decades, it became obvious that a deeper understanding of power grids from the complex system perspective is necessary. That the perspective of complex systems science adds important notions to help understanding power grids better, in particular their stability. The physical grid itself—the transmission lines connecting various power stations, substations, consumers, etc—constitutes a complex coupling structure of the dynamical system. This can be well-described within the framework of complex networks theory. In addition [6] define the notion of reliability of information processing in close relation to stability They find that there are certain motifs suppressing fluctuations and tending to synchronize the dynamics of single elements. We propose a logistic regression model aiming to predict the individual single-node basin stability using only a small set of network characteristics
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
