Deciphering the imprint of topology on nonlinear dynamical network stability

dc.bibliographicCitation.volume19
dc.contributor.authorNitzbon, J.
dc.contributor.authorSchultz, P.
dc.contributor.authorHeitzig, J.
dc.contributor.authorHellmann, F.
dc.date.accessioned2017-06-26T23:57:10Z
dc.date.available2019-06-28T10:35:11Z
dc.date.issued2017
dc.description.abstractCoupled oscillator networks show complex interrelations between topological characteristics of the network and the nonlinear stability of single nodes with respect to large but realistic perturbations. We extend previous results on these relations by incorporating sampling-based measures of the transient behaviour of the system, its survivability, as well as its asymptotic behaviour, its basin stability. By combining basin stability and survivability we uncover novel, previously unknown asymptotic states with solitary, desynchronized oscillators which are rotating with a frequency different from their natural one. They occur almost exclusively after perturbations at nodes with specific topological properties. More generally we confirm and significantly refine the results on the distinguished role tree-shaped appendices play for nonlinear stability. We find a topological classification scheme for nodes located in such appendices, that exactly separates them according to their stability properties, thus establishing a strong link between topology and dynamics. Hence, the results can be used for the identification of vulnerable nodes in power grids or other coupled oscillator networks. From this classification we can derive general design principles for resilient power grids. We find that striving for homogeneous network topologies facilitates a better performance in terms of nonlinear dynamical network stability. While the employed second-order Kuramoto-like model is parametrised to be representative for power grids, we expect these insights to transfer to other critical infrastructure systems or complex network dynamics appearing in various other fields.eng
dc.description.versionpublishedVersioneng
dc.formatapplication/pdf
dc.identifier.urihttps://doi.org/10.34657/232
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/3828
dc.language.isoengeng
dc.publisherBristol : IOP Publishingeng
dc.relation.doihttps://doi.org/10.1088/1367-2630/aa6321
dc.relation.ispartofseriesNew Journal of Physics, Volume 19eng
dc.rights.licenseCC BY 3.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/eng
dc.subjectCoupled ocscillator networkseng
dc.subjectnetwork stabilityeng
dc.subjectnetwork topologyeng
dc.subjectpower gridseng
dc.subjectbasin stabilityeng
dc.subjectsurvivabilityeng
dc.subjectsecond-order Kuramoto modeleng
dc.subject.ddc500eng
dc.titleDeciphering the imprint of topology on nonlinear dynamical network stabilityeng
dc.typearticleeng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitleNew Journal of Physicseng
tib.accessRightsopenAccesseng
wgl.contributorPIKeng
wgl.subjectUmweltwissenschafteneng
wgl.typeZeitschriftenartikeleng
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Nitzbon_2017_New_J._Phys._19_033029.pdf
Size:
13 MB
Format:
Adobe Portable Document Format
Description: