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Synchronisation in complex networks with applications to power grids

In this thesis, we present several novel theoretical results in complex networks, most of which benefit from extensions of existing methods of analysis in electrical engineering. These results not only contribute to a better characterisation of the topology and structure of complex networks, but also provide a new way to study complex systems by modelling them as a flow network to determine how nodes nonlocally interact as a function of the adjacent physical laws. We also contribute towards a better understanding of how frequency synchronisation (FS) in coupled phase oscillator networks comes about by revealing the fundamental mechanisms and determinant conditions for nodes to become FS. Moreover, we design a scheme to control explosive synchronisation. Equipped with the theoretical knowledge obtained from the study of phase oscillator networks, we reveal the mechanism behind the onset of FS in realistic models of power grids and the causes behind frequency collapse. Furthermore, we put forward advanced control techniques and novel prediction methods to prevent blackouts from happening in those models. These results might help engineers to construct a stable, economic and efficient smart power grid in the near future. The breakthroughs in this thesis build up a bridge which, on the one hand, promotes the progress of the research in the fields of complex networks and synchronization by borrowing methods from electrical engineering and extending them to the treatment of complex networks, and on the other hand, aids engineers to efficiently solve some specific problems in smart grids based on the knowledge of approaches coming from the area of complex systems. Therefore, this thesis bridges the gap between engineering and physics by identifying, explaining and extending interdisciplinary approaches from these two disciplines to better understand models and networks considered within these fields.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:715489
Date January 2017
CreatorsWang, Chengwei
PublisherUniversity of Aberdeen
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=232252

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